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data/external/evidence/formal/derived_summaries/scripts/build_formal_evidence_summaries.py

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+from __future__ import annotations
+
+import csv
+import hashlib
+import math
+from collections import defaultdict
+from pathlib import Path
+from typing import Iterable, Mapping
+
+import numpy as np
+import pandas as pd
+from scipy.optimize import curve_fit
+
+from reasoning_meme.analysis.boundary_cross_validation import (
+    boundary_binned_auc_rows,
+    ranking_pair_counts,
+)
+from reasoning_meme.diffusion.cost_efficiency_16sample import _strategy_correct
+
+
+ROOT = Path(__file__).resolve().parents[5]
+OUT_DIR = ROOT / "manuscript" / "evidence" / "formal" / "derived_summaries"
+
+FOUR_BENCH_BINNED = ROOT / "results" / "summaries" / "boundary_cross_model_2x2_binned_auc.csv"
+HLE_QA_MODEL_PAIR_BINNED = ROOT / "results" / "formal" / "hle_qa_selector_boundary" / "summaries" / "hle_qa_model_pair_binned_auc.csv"
+HLE_QA_ROOT = ROOT / "results" / "formal" / "hle_qa_selector_boundary"
+
+FIVE_BENCH_ROOT = ROOT / "results" / "formal" / "five_benchmark_selector_boundary"
+MEDIUM_SAMPLE_BANK_DIR = (
+    ROOT
+    / "results"
+    / "formal"
+    / "medium_thinking_sample_banks"
+    / "generated_pools"
+    / "mimo_medium_generated"
+)
+SAMPLE_BANK_DIR_OVERRIDES = {"mimo_medium": MEDIUM_SAMPLE_BANK_DIR}
+GLOBAL_REPLAY_ROOT = ROOT / "results" / "formal" / "global_leaderboard_diffusion"
+MINORITY_ROOT = ROOT / "results" / "formal" / "prospective_diffusion_minority_evidence"
+PERTURB_ROOT = ROOT / "results" / "formal" / "prospective_diffusion_perturbation"
+POOL_COST_ROOT = ROOT / "results" / "formal" / "five_benchmark_cost_efficiency"
+
+K16_MATCHED_COHORTS = {
+    "mimo_no_think": {
+        "generator": "mimo",
+        "pools": (
+            POOL_COST_ROOT
+            / "raw"
+            / "populations"
+            / "baseline_pool_size_v1"
+            / "pools"
+            / "generator=mimo"
+            / "strict_common_natural_k16"
+            / "pools.csv"
+        ),
+        "rankings": (
+            POOL_COST_ROOT
+            / "raw"
+            / "populations"
+            / "baseline_pool_size_v1"
+            / "rankings"
+            / "distribution=natural"
+            / "k=16"
+            / "generator=mimo"
+            / "selector=deepseek"
+            / "details.csv"
+        ),
+    },
+    "mimo_medium_thinking": {
+        "generator": "mimo_medium",
+        "pools": (
+            POOL_COST_ROOT
+            / "raw"
+            / "populations"
+            / "mimo_medium_v1"
+            / "pools"
+            / "distribution=natural"
+            / "k=16"
+            / "pools.csv"
+        ),
+        "rankings": (
+            POOL_COST_ROOT
+            / "raw"
+            / "populations"
+            / "mimo_medium_v1"
+            / "rankings"
+            / "distribution=natural"
+            / "k=16"
+            / "generator=mimo_medium"
+            / "selector=deepseek"
+            / "details.csv"
+        ),
+    },
+}
+K16_STRATEGY_SEED = 20260701
+
+AVAILABILITY_METRIC = "question_sample_bank_correct_rate"
+AVAILABILITY_DEFINITION = "correct parse-valid generations divided by all parse-valid generations for the same question"
+MIDPOINT_DEFINITION = "p_gen where the fitted rank AUC reaches 0.5 + A/2"
+BOOTSTRAP_REPLICATES = 1000
+BOOTSTRAP_SEED = 20260710
+TRUTHY = {"1", "true", "t", "yes", "y"}
+
+MODEL_PAIR_LABELS = {
+    "deepseek->deepseek": "DeepSeek generated / DeepSeek judge",
+    "deepseek->mimo": "DeepSeek generated / Mimo no-think judge",
+    "mimo->deepseek": "Mimo no-think generated / DeepSeek judge",
+    "mimo->mimo": "Mimo no-think generated / Mimo no-think judge",
+    "deepseek->mimo_medium": "DeepSeek generated / Mimo medium-thinking judge",
+    "mimo_medium->deepseek": "Mimo medium-thinking generated / DeepSeek judge",
+    "mimo_medium->mimo_medium": "Mimo medium-thinking generated / Mimo medium-thinking judge",
+}
+
+MODEL_PAIR_SPECS = (
+    ("deepseek", "deepseek", MODEL_PAIR_LABELS["deepseek->deepseek"]),
+    ("deepseek", "mimo", MODEL_PAIR_LABELS["deepseek->mimo"]),
+    ("mimo", "deepseek", MODEL_PAIR_LABELS["mimo->deepseek"]),
+    ("mimo", "mimo", MODEL_PAIR_LABELS["mimo->mimo"]),
+    ("deepseek", "mimo_medium", MODEL_PAIR_LABELS["deepseek->mimo_medium"]),
+    ("mimo_medium", "deepseek", MODEL_PAIR_LABELS["mimo_medium->deepseek"]),
+    ("mimo_medium", "mimo_medium", MODEL_PAIR_LABELS["mimo_medium->mimo_medium"]),
+)
+
+MODELING_BENCHMARKS = ("mmlu_pro", "gpqa", "medxpertqa", "musr")
+EXTERNAL_MC_BENCHMARKS = ("hle_text_mc",)
+
+MODEL_PAIR_IDS = tuple(
+    f"{generator}->{judge}" for generator, judge, _label in MODEL_PAIR_SPECS
+)
+
+MEDIUM_CONTRASTS = {
+    "generator_bank_under_ds_judge": (
+        "mimo->deepseek",
+        "mimo_medium->deepseek",
+        "question_support_highly_matched_generated_traces_differ",
+    ),
+    "judge_thinking_on_ds_bank": (
+        "deepseek->mimo",
+        "deepseek->mimo_medium",
+        "same_candidate_bank",
+    ),
+    "self_bundle": (
+        "mimo->mimo",
+        "mimo_medium->mimo_medium",
+        "compound_generator_and_judge_change",
+    ),
+}
+
+BENCHMARK_LABELS = {
+    "__global__": "All benchmarks",
+    "mmlu_pro": "MMLU-Pro",
+    "gpqa": "GPQA",
+    "medxpertqa": "MedXpertQA",
+    "musr": "MuSR",
+    "hle_text_mc": "HLE MC",
+    "hle_text_qa_verified": "HLE QA",
+}
+
+STRATEGY_LABELS = {
+    "direct_single_random": "Single sampled trace",
+    "shuffled_rank_soft_copy": "Shuffled ranking control",
+    "majority_vote": "Majority vote",
+    "rank_soft_copy": "Judge-guided rank copy",
+    "rank_top1_copy": "Judge top-1 copy",
+}
+
+
+def rel(path: Path) -> str:
+    try:
+        return str(path.relative_to(ROOT))
+    except ValueError:
+        return str(path)
+
+
+def file_sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as handle:
+        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def sample_bank_path(
+    formal_root: Path,
+    generator: str,
+    benchmark: str,
+    *,
+    sample_bank_dirs: Mapping[str, Path] | None = None,
+) -> Path:
+    override = (sample_bank_dirs or {}).get(generator)
+    if override is not None:
+        path = Path(override) / benchmark / "sample_bank.csv"
+    else:
+        path = (
+            formal_root
+            / "generated_pools"
+            / f"{generator}_generated"
+            / benchmark
+            / "sample_bank.csv"
+        )
+    if not path.is_file():
+        raise FileNotFoundError(
+            f"Missing sample bank for {generator}/{benchmark}: {path}"
+        )
+    return path
+
+
+def sigmoid(x: np.ndarray) -> np.ndarray:
+    return 1.0 / (1.0 + np.exp(-x))
+
+
+def logit(p: np.ndarray) -> np.ndarray:
+    p = np.clip(p, 1e-4, 1 - 1e-4)
+    return np.log(p / (1 - p))
+
+
+def auc_boundary(p: np.ndarray, a: float, k: float, midpoint: float) -> np.ndarray:
+    return 0.5 + a * sigmoid(k * (logit(p) - logit(np.asarray(midpoint))))
+
+
+def fit_boundary(df: pd.DataFrame) -> dict[str, float | str]:
+    data = df[(df["pairs"] > 0) & df["auc"].notna()].copy()
+    if len(data) < 4:
+        return {"fit_status": "too_few_bins", "A": np.nan, "k": np.nan, "midpoint": np.nan, "weighted_r2": np.nan}
+
+    x_column = "p_gen_bin_mid" if "p_gen_bin_mid" in data.columns else "p_correct_bin_mid"
+    x = data[x_column].to_numpy(dtype=float)
+    y = data["auc"].to_numpy(dtype=float)
+    w = data["pairs"].to_numpy(dtype=float)
+    initial_a = float(np.clip(np.nanmax(y) - 0.5, 0.02, 0.49))
+    above = data[data["auc"] >= 0.70]
+    initial_midpoint = float(above[x_column].iloc[0]) if len(above) else float(np.median(x))
+    initial_midpoint = float(np.clip(initial_midpoint, 0.01, 0.95))
+    sigma = 1.0 / np.sqrt(np.maximum(w, 1.0))
+    try:
+        params, _ = curve_fit(
+            auc_boundary,
+            x,
+            y,
+            p0=(initial_a, 2.0, initial_midpoint),
+            sigma=sigma,
+            bounds=([0.0, 0.01, 0.001], [0.55, 20.0, 0.999]),
+            maxfev=20000,
+        )
+        yhat = auc_boundary(x, *params)
+        ybar = float(np.average(y, weights=w))
+        sse = float(np.sum(w * (y - yhat) ** 2))
+        sst = float(np.sum(w * (y - ybar) ** 2))
+        r2 = np.nan if sst <= 0 else 1.0 - sse / sst
+        return {
+            "fit_status": "ok",
+            "A": float(params[0]),
+            "k": float(params[1]),
+            "midpoint": float(params[2]),
+            "weighted_r2": float(r2),
+        }
+    except Exception as exc:  # pragma: no cover - recorded into summary table.
+        return {"fit_status": f"fit_failed:{type(exc).__name__}", "A": np.nan, "k": np.nan, "midpoint": np.nan, "weighted_r2": np.nan}
+
+
+def classify_fit_quality(weighted_r2: float | None) -> str:
+    """Separate numerical optimizer success from an interpretable boundary fit."""
+
+    if weighted_r2 is None or not np.isfinite(float(weighted_r2)):
+        return "not_interpretable"
+    if float(weighted_r2) >= 0.75:
+        return "strong_boundary_fit"
+    if float(weighted_r2) >= 0.50:
+        return "usable_boundary_fit"
+    return "low_r2_diagnostic"
+
+
+def bin_midpoint(value: float, bin_width: float = 0.02) -> float:
+    clipped = min(max(value, 1e-12), 1.0)
+    index = min(max(int(math.ceil(clipped / bin_width) - 1), 0), int(round(1 / bin_width)) - 1)
+    return round(index * bin_width + bin_width / 2.0, 2)
+
+
+def tag_availability_metric(frame: pd.DataFrame) -> pd.DataFrame:
+    """Make the manuscript x-axis definition explicit while retaining legacy columns."""
+
+    tagged = frame.copy()
+    for column in ("p_correct_bin_mid", "wins", "pairs", "auc", "n_pools", "n_parse_failed"):
+        if column in tagged.columns:
+            tagged[column] = pd.to_numeric(tagged[column], errors="coerce")
+    if "p_gen_bin_mid" not in tagged.columns:
+        tagged["p_gen_bin_mid"] = tagged["p_correct_bin_mid"].astype(float)
+    tagged["availability_metric"] = AVAILABILITY_METRIC
+    tagged["availability_definition"] = AVAILABILITY_DEFINITION
+    return tagged
+
+
+def validate_availability_frame(frame: pd.DataFrame, name: str) -> None:
+    required = {"p_correct_bin_mid", "p_gen_bin_mid", "availability_metric"}
+    missing = required - set(frame.columns)
+    if missing:
+        raise ValueError(f"{name} is missing availability fields: {sorted(missing)}")
+    metrics = set(frame["availability_metric"].dropna().astype(str))
+    if metrics != {AVAILABILITY_METRIC}:
+        raise ValueError(f"{name} mixes availability metrics: {sorted(metrics)}")
+    legacy = pd.to_numeric(frame["p_correct_bin_mid"], errors="coerce")
+    p_gen = pd.to_numeric(frame["p_gen_bin_mid"], errors="coerce")
+    comparable = legacy.notna() & p_gen.notna()
+    if not np.allclose(legacy[comparable], p_gen[comparable], atol=1e-12, rtol=0):
+        raise ValueError(f"{name} contains inconsistent legacy p_correct and p_gen bins")
+
+
+def hle_mc_model_pair_binned_auc() -> pd.DataFrame:
+    rows = boundary_binned_auc_rows(
+        formal_root=FIVE_BENCH_ROOT,
+        grouping="model_pair",
+        benchmarks=("hle_text_mc",),
+        regimes=("natural", "balanced"),
+        bin_width=0.02,
+        sample_bank_dirs=SAMPLE_BANK_DIR_OVERRIDES,
+    )
+    if not rows:
+        raise ValueError("No HLE MC selector-boundary rows were derived from the formal sample bank")
+    return tag_availability_metric(pd.DataFrame(rows))
+
+
+def model_pair_binned_auc_by_benchmark(bin_width: float) -> pd.DataFrame:
+    """Derive seven-cell model-pair AUC bins separately for all five benchmarks."""
+
+    frames: list[pd.DataFrame] = []
+    for benchmark in (*MODELING_BENCHMARKS, *EXTERNAL_MC_BENCHMARKS):
+        rows = boundary_binned_auc_rows(
+            formal_root=FIVE_BENCH_ROOT,
+            grouping="model_pair",
+            benchmarks=(benchmark,),
+            regimes=("natural", "balanced"),
+            bin_width=bin_width,
+            sample_bank_dirs=SAMPLE_BANK_DIR_OVERRIDES,
+        )
+        if not rows:
+            raise ValueError(f"No selector-boundary rows for {benchmark}/{bin_width=}")
+        frame = tag_availability_metric(pd.DataFrame(rows))
+        frame = frame[frame["series_id"].isin(MODEL_PAIR_IDS)].copy()
+        observed = set(frame["series_id"].astype(str))
+        missing = set(MODEL_PAIR_IDS) - observed
+        if missing:
+            raise ValueError(
+                f"Missing declared model-pair rows for {benchmark}/{bin_width=}: "
+                f"{sorted(missing)}"
+            )
+        frame["benchmark_scope"] = benchmark
+        frame["benchmark"] = benchmark
+        frame["bin_width"] = bin_width
+        validate_availability_frame(frame, f"{benchmark} model-pair boundary")
+        frames.append(frame)
+    return pd.concat(frames, ignore_index=True)
+
+
+def aggregate_model_pair_bins(
+    benchmark_bins: pd.DataFrame,
+    benchmarks: Iterable[str],
+    benchmark_scope: str,
+) -> pd.DataFrame:
+    """Pool already-binned pair counts without changing the p_gen definition."""
+
+    selected = benchmark_bins[benchmark_bins["benchmark"].isin(tuple(benchmarks))].copy()
+    if selected.empty:
+        raise ValueError(f"No benchmark bins for {benchmark_scope}")
+    group_columns = [
+        "pool_regime",
+        "generator",
+        "judge",
+        "series_id",
+        "series_label",
+        "p_gen_bin_mid",
+        "p_correct_bin_mid",
+        "bin_width",
+        "availability_metric",
+        "availability_definition",
+    ]
+    pooled = (
+        selected.groupby(group_columns, as_index=False, dropna=False)
+        .agg(
+            wins=("wins", "sum"),
+            pairs=("pairs", "sum"),
+            n_pools=("n_pools", "sum"),
+            n_parse_failed=("n_parse_failed", "sum"),
+        )
+        .sort_values(["pool_regime", "series_id", "p_gen_bin_mid"])
+    )
+    pooled["auc"] = pooled["wins"] / pooled["pairs"]
+    pooled["grouping"] = "model_pair"
+    pooled["benchmark_scope"] = benchmark_scope
+    pooled["benchmark"] = "__pooled__"
+    validate_availability_frame(pooled, benchmark_scope)
+    return pooled
+
+
+def fit_model_pair_bins(binned: pd.DataFrame) -> pd.DataFrame:
+    """Fit each benchmark-scope, regime and model-pair curve independently."""
+
+    rows: list[dict[str, object]] = []
+    group_columns = [
+        "benchmark_scope",
+        "benchmark",
+        "pool_regime",
+        "generator",
+        "judge",
+        "series_id",
+        "series_label",
+        "bin_width",
+    ]
+    for keys, group in binned.groupby(group_columns, dropna=False):
+        (
+            benchmark_scope,
+            benchmark,
+            regime,
+            generator,
+            judge,
+            series_id,
+            series_label,
+            bin_width,
+        ) = keys
+        fit = fit_boundary(group)
+        pair_total = int(group["pairs"].sum())
+        mean_auc = (
+            float(group["wins"].sum() / pair_total)
+            if pair_total > 0
+            else np.nan
+        )
+        rows.append(
+            {
+                "benchmark_scope": benchmark_scope,
+                "benchmark": benchmark,
+                "regime": regime,
+                "generator": generator,
+                "judge": judge,
+                "model_pair": series_id,
+                "model_pair_label": MODEL_PAIR_LABELS.get(
+                    str(series_id), str(series_label)
+                ),
+                "bin_width": float(bin_width),
+                "A": fit["A"],
+                "slope_beta": fit["k"],
+                "midpoint": fit["midpoint"],
+                "midpoint_percent": (
+                    np.nan
+                    if pd.isna(fit["midpoint"])
+                    else 100.0 * float(fit["midpoint"])
+                ),
+                "weighted_r2": fit["weighted_r2"],
+                "fit_status": fit["fit_status"],
+                "fit_quality": classify_fit_quality(
+                    pd.to_numeric(pd.Series([fit["weighted_r2"]]), errors="coerce").iloc[0]
+                ),
+                "mean_auc": mean_auc,
+                "n_bins": int((group["pairs"] > 0).sum()),
+                "n_pairs": pair_total,
+                "n_pools": int(group["n_pools"].sum()),
+                "n_parse_failed": int(group["n_parse_failed"].sum()),
+                "availability_metric": AVAILABILITY_METRIC,
+                "availability_definition": AVAILABILITY_DEFINITION,
+                "source_file": rel(FIVE_BENCH_ROOT),
+            }
+        )
+    return pd.DataFrame(rows).sort_values(
+        ["benchmark_scope", "bin_width", "regime", "model_pair"]
+    )
+
+
+def fit_on_common_bins(
+    binned: pd.DataFrame,
+    left_pair: str,
+    right_pair: str,
+) -> tuple[dict[str, float | str], dict[str, float | str], int]:
+    """Refit two curves on identical p_gen bin support."""
+
+    left = binned[binned["series_id"] == left_pair].copy()
+    right = binned[binned["series_id"] == right_pair].copy()
+    common = sorted(set(left["p_gen_bin_mid"]) & set(right["p_gen_bin_mid"]))
+    if len(common) < 4:
+        raise ValueError(
+            f"Too few common bins for {left_pair} versus {right_pair}: {len(common)}"
+        )
+    return (
+        fit_boundary(left[left["p_gen_bin_mid"].isin(common)]),
+        fit_boundary(right[right["p_gen_bin_mid"].isin(common)]),
+        len(common),
+    )
+
+
+def build_medium_sensitivity_summary(
+    binned: pd.DataFrame,
+    fits: pd.DataFrame,
+) -> pd.DataFrame:
+    """Summarize bounded no-think-versus-medium sensitivity contrasts."""
+
+    rows: list[dict[str, object]] = []
+    pooled_scopes = (
+        "four_benchmark_modeling_set",
+        "five_benchmark_sensitivity",
+    )
+    for scope in pooled_scopes:
+        for bin_width in (0.02, 0.05):
+            for regime in ("natural", "balanced"):
+                subset = binned[
+                    (binned["benchmark_scope"] == scope)
+                    & np.isclose(binned["bin_width"], bin_width)
+                    & (binned["pool_regime"] == regime)
+                ]
+                fit_subset = fits[
+                    (fits["benchmark_scope"] == scope)
+                    & np.isclose(fits["bin_width"], bin_width)
+                    & (fits["regime"] == regime)
+                ].set_index("model_pair")
+                for contrast, (left_pair, right_pair, caveat) in MEDIUM_CONTRASTS.items():
+                    left = fit_subset.loc[left_pair]
+                    right = fit_subset.loc[right_pair]
+                    for support_mode in ("all_bins", "common_bins"):
+                        if support_mode == "all_bins":
+                            left_fit = left
+                            right_fit = right
+                            n_common_bins = np.nan
+                            left_mean_auc = float(left["mean_auc"])
+                            right_mean_auc = float(right["mean_auc"])
+                        else:
+                            left_fit, right_fit, n_common_bins = fit_on_common_bins(
+                                subset,
+                                left_pair,
+                                right_pair,
+                            )
+                            left_bins = subset[subset["series_id"] == left_pair]
+                            right_bins = subset[subset["series_id"] == right_pair]
+                            common = set(left_bins["p_gen_bin_mid"]) & set(
+                                right_bins["p_gen_bin_mid"]
+                            )
+                            left_common = left_bins[left_bins["p_gen_bin_mid"].isin(common)]
+                            right_common = right_bins[right_bins["p_gen_bin_mid"].isin(common)]
+                            left_mean_auc = float(
+                                left_common["wins"].sum() / left_common["pairs"].sum()
+                            )
+                            right_mean_auc = float(
+                                right_common["wins"].sum() / right_common["pairs"].sum()
+                            )
+                        left_r2 = float(left_fit["weighted_r2"])
+                        right_r2 = float(right_fit["weighted_r2"])
+                        left_midpoint = float(left_fit["midpoint"])
+                        right_midpoint = float(right_fit["midpoint"])
+                        rows.append(
+                            {
+                                "benchmark_scope": scope,
+                                "regime": regime,
+                                "bin_width": bin_width,
+                                "contrast": contrast,
+                                "support_mode": support_mode,
+                                "left_model_pair": left_pair,
+                                "right_model_pair": right_pair,
+                                "left_weighted_r2": left_r2,
+                                "right_weighted_r2": right_r2,
+                                "delta_weighted_r2": right_r2 - left_r2,
+                                "left_mean_auc": left_mean_auc,
+                                "right_mean_auc": right_mean_auc,
+                                "delta_mean_auc": right_mean_auc - left_mean_auc,
+                                "left_midpoint": left_midpoint,
+                                "right_midpoint": right_midpoint,
+                                "delta_midpoint": right_midpoint - left_midpoint,
+                                "n_common_bins": n_common_bins,
+                                "comparison_caveat": caveat,
+                                "availability_metric": AVAILABILITY_METRIC,
+                            }
+                        )
+    return pd.DataFrame(rows)
+
+
+def build_model_pair_source_manifest() -> pd.DataFrame:
+    """Record the actual files and parse counts used by the seven-cell analysis."""
+
+    rows: list[dict[str, object]] = []
+    sweep_path = FIVE_BENCH_ROOT / "boundary_mimo_medium_2x2_sweep_manifest.csv"
+    sweep_lookup: dict[tuple[str, str, str, str], str] = {}
+    if sweep_path.is_file():
+        sweep = pd.read_csv(sweep_path)
+        for row in sweep.itertuples(index=False):
+            sweep_lookup[
+                (
+                    str(row.generator),
+                    str(row.judge),
+                    str(row.benchmark),
+                    str(row.regime),
+                )
+            ] = str(row.status)
+
+    sample_counts: dict[tuple[str, str], dict[str, object]] = {}
+    for generator, judge, _label in MODEL_PAIR_SPECS:
+        for benchmark in (*MODELING_BENCHMARKS, *EXTERNAL_MC_BENCHMARKS):
+            sample_path = sample_bank_path(
+                FIVE_BENCH_ROOT,
+                generator,
+                benchmark,
+                sample_bank_dirs=SAMPLE_BANK_DIR_OVERRIDES,
+            )
+            sample_key = (generator, benchmark)
+            if sample_key not in sample_counts:
+                sample = pd.read_csv(
+                    sample_path,
+                    usecols=["question_id", "generation_parse_ok"],
+                )
+                parse_ok = sample["generation_parse_ok"].astype(str).str.lower().isin(TRUTHY)
+                sample_counts[sample_key] = {
+                    "sample_file_rows": int(len(sample)),
+                    "sample_parse_ok_rows": int(parse_ok.sum()),
+                    "sample_questions": int(
+                        sample.loc[parse_ok, "question_id"].nunique()
+                    ),
+                    "sample_file_size": int(sample_path.stat().st_size),
+                    "sample_sha256": file_sha256(sample_path),
+                }
+            sample_info = sample_counts[sample_key]
+            for regime in ("natural", "balanced"):
+                ranking_path = (
+                    FIVE_BENCH_ROOT
+                    / "selector_rankings"
+                    / f"{judge}_judge"
+                    / f"{generator}_generated"
+                    / benchmark
+                    / f"{regime}_ranking.csv"
+                )
+                summary_path = ranking_path.with_name(f"{regime}_ranking_summary.csv")
+                if not ranking_path.is_file() or not summary_path.is_file():
+                    raise FileNotFoundError(
+                        f"Missing declared ranking source for {generator}->{judge}/"
+                        f"{benchmark}/{regime}: {ranking_path}"
+                    )
+                summary = pd.read_csv(summary_path).iloc[0]
+                n_rows = int(summary["n_rows"])
+                n_parse_ok = int(summary["n_parse_ok"])
+                ranking_sha256 = file_sha256(ranking_path)
+                source_signature = hashlib.sha256(
+                    (
+                        f"{sample_info['sample_sha256']}:{ranking_sha256}:"
+                        f"{generator}:{judge}:{benchmark}:{regime}"
+                    ).encode("utf-8")
+                ).hexdigest()
+                rows.append(
+                    {
+                        "generator": generator,
+                        "judge": judge,
+                        "model_pair": f"{generator}->{judge}",
+                        "benchmark": benchmark,
+                        "regime": regime,
+                        "artifact_status": "present",
+                        "manifest_status": sweep_lookup.get(
+                            (generator, judge, benchmark, regime),
+                            "formal_snapshot_not_in_incremental_sweep",
+                        ),
+                        "sample_source_kind": (
+                            "canonical_medium_thinking_sample_bank"
+                            if generator == "mimo_medium"
+                            else "five_benchmark_selector_boundary_sample_bank"
+                        ),
+                        "sample_bank_path": rel(sample_path),
+                        **sample_info,
+                        "ranking_path": rel(ranking_path),
+                        "ranking_summary_path": rel(summary_path),
+                        "ranking_file_size": int(ranking_path.stat().st_size),
+                        "ranking_sha256": ranking_sha256,
+                        "ranking_rows": n_rows,
+                        "ranking_parse_ok": n_parse_ok,
+                        "ranking_parse_failed": n_rows - n_parse_ok,
+                        "ranking_parse_ok_rate": n_parse_ok / n_rows if n_rows else np.nan,
+                        "source_signature": source_signature,
+                    }
+                )
+    return pd.DataFrame(rows)
+
+
+def build_model_pair_boundary_summaries() -> tuple[pd.DataFrame, pd.DataFrame]:
+    """Write canonical seven-cell boundary data for figures and tables."""
+
+    binned_frames: list[pd.DataFrame] = []
+    for bin_width in (0.02, 0.05):
+        benchmark_bins = model_pair_binned_auc_by_benchmark(bin_width)
+        binned_frames.append(benchmark_bins)
+        binned_frames.append(
+            aggregate_model_pair_bins(
+                benchmark_bins,
+                MODELING_BENCHMARKS,
+                "four_benchmark_modeling_set",
+            )
+        )
+        binned_frames.append(
+            aggregate_model_pair_bins(
+                benchmark_bins,
+                (*MODELING_BENCHMARKS, *EXTERNAL_MC_BENCHMARKS),
+                "five_benchmark_sensitivity",
+            )
+        )
+    binned = pd.concat(binned_frames, ignore_index=True)
+    binned["series_label"] = binned.apply(
+        lambda row: MODEL_PAIR_LABELS.get(str(row["series_id"]), str(row["series_label"])),
+        axis=1,
+    )
+    fits = fit_model_pair_bins(binned)
+    sensitivity = build_medium_sensitivity_summary(binned, fits)
+    manifest = build_model_pair_source_manifest()
+
+    binned.to_csv(
+        OUT_DIR / "selector_boundary_model_pair_binned_auc.csv",
+        index=False,
+    )
+    fits.to_csv(
+        OUT_DIR / "selector_boundary_model_pair_fit_summary.csv",
+        index=False,
+    )
+    sensitivity.to_csv(
+        OUT_DIR / "selector_boundary_medium_sensitivity_summary.csv",
+        index=False,
+    )
+    manifest.to_csv(
+        OUT_DIR / "selector_boundary_model_pair_source_manifest.csv",
+        index=False,
+    )
+    return binned, fits
+
+
+def add_fit_rows(
+    binned: pd.DataFrame,
+    benchmark_scope: str,
+    benchmark_family: str,
+    source_file: Path,
+    label_source: str,
+    manuscript_role: str,
+    caveat: str,
+) -> list[dict[str, object]]:
+    out: list[dict[str, object]] = []
+    group_cols = ["pool_regime", "benchmark", "generator", "judge", "series_id", "series_label"]
+    for keys, group in binned.groupby(group_cols, dropna=False):
+        regime, benchmark, generator, judge, series_id, series_label = keys
+        fit = fit_boundary(group)
+        pair_total = int(group["pairs"].sum())
+        mean_auc = (
+            float(group["wins"].sum() / pair_total)
+            if pair_total > 0
+            else np.nan
+        )
+        out.append(
+            {
+                "summary_id": f"{benchmark_scope}:{regime}:{series_id}",
+                "manuscript_role": manuscript_role,
+                "benchmark_scope": benchmark_scope,
+                "benchmark_family": benchmark_family,
+                "benchmark": benchmark,
+                "regime": regime,
+                "generator": generator,
+                "judge": judge,
+                "model_pair": series_id,
+                "model_pair_label": MODEL_PAIR_LABELS.get(series_id, str(series_label)),
+                "label_source": label_source,
+                "label_caveat": caveat,
+                "availability_metric": AVAILABILITY_METRIC,
+                "availability_definition": AVAILABILITY_DEFINITION,
+                "midpoint_definition": MIDPOINT_DEFINITION,
+                "A": fit["A"],
+                "k": fit["k"],
+                "slope_beta": fit["k"],
+                "midpoint": fit["midpoint"],
+                "midpoint_percent": np.nan if pd.isna(fit["midpoint"]) else 100.0 * float(fit["midpoint"]),
+                "weighted_r2": fit["weighted_r2"],
+                "fit_status": fit["fit_status"],
+                "fit_quality": classify_fit_quality(
+                    pd.to_numeric(pd.Series([fit["weighted_r2"]]), errors="coerce").iloc[0]
+                ),
+                "mean_auc": mean_auc,
+                "n_bins": int((group["pairs"] > 0).sum()),
+                "n_pairs": pair_total,
+                "n_pools": int(group["n_pools"].sum()),
+                "n_parse_failed": int(group["n_parse_failed"].sum()),
+                "source_file": rel(source_file),
+            }
+        )
+    return out
+
+
+def _is_truthy(value: object) -> bool:
+    return str(value or "").strip().lower() in TRUTHY
+
+
+def _split_ids(value: object) -> list[str]:
+    return [part.strip() for part in str(value or "").split("|") if part.strip()]
+
+
+def question_level_selector_counts(
+    formal_root: Path,
+    benchmarks: Iterable[str],
+    regime: str,
+    *,
+    generator: str = "deepseek",
+    judge: str = "deepseek",
+    sample_bank_dirs: Mapping[str, Path] | None = None,
+) -> pd.DataFrame:
+    """Return pairwise ranking counts at the independent question level."""
+
+    records: list[dict[str, object]] = []
+    for benchmark in benchmarks:
+        sample_path = sample_bank_path(
+            formal_root,
+            generator,
+            benchmark,
+            sample_bank_dirs=sample_bank_dirs,
+        )
+        ranking_path = (
+            formal_root
+            / "selector_rankings"
+            / f"{judge}_judge"
+            / f"{generator}_generated"
+            / benchmark
+            / f"{regime}_ranking.csv"
+        )
+        if not sample_path.exists() or not ranking_path.exists():
+            raise FileNotFoundError(
+                "Missing formal selector input for "
+                f"{generator}->{judge}/{benchmark}/{regime}: "
+                f"sample={sample_path}, ranking={ranking_path}"
+            )
+
+        totals: dict[str, int] = defaultdict(int)
+        corrects: dict[str, int] = defaultdict(int)
+        with sample_path.open(newline="", encoding="utf-8") as handle:
+            for row in csv.DictReader(handle):
+                if "generation_parse_ok" in row and not _is_truthy(row.get("generation_parse_ok")):
+                    continue
+                question_id = str(row.get("question_id", "")).strip()
+                label = str(row.get("label", "")).strip()
+                if not question_id or label not in {"0", "1"}:
+                    continue
+                totals[question_id] += 1
+                corrects[question_id] += int(label)
+        p_gen = {question_id: corrects[question_id] / total for question_id, total in totals.items() if total}
+
+        aggregates: dict[tuple[str, float], dict[str, int]] = defaultdict(
+            lambda: {
+                "wins": 0,
+                "pairs": 0,
+                "n_pools": 0,
+                "n_parse_failed": 0,
+            }
+        )
+        missing_availability: set[str] = set()
+        with ranking_path.open(newline="", encoding="utf-8") as handle:
+            for row in csv.DictReader(handle):
+                question_id = str(row.get("question_id", "")).strip()
+                availability = p_gen.get(question_id)
+                if availability is None:
+                    if question_id:
+                        missing_availability.add(question_id)
+                    continue
+                key = (question_id, bin_midpoint(availability))
+                if not _is_truthy(row.get("parse_ok")):
+                    aggregates[key]["n_parse_failed"] += 1
+                    continue
+                wins, pairs = ranking_pair_counts(
+                    correct_meme_ids=set(_split_ids(row.get("correct_meme_id"))),
+                    candidate_order=_split_ids(row.get("candidate_order")),
+                    ranking=_split_ids(row.get("ranking")),
+                )
+                if pairs <= 0:
+                    continue
+                aggregates[key]["wins"] += wins
+                aggregates[key]["pairs"] += pairs
+                aggregates[key]["n_pools"] += 1
+
+        if missing_availability:
+            preview = ", ".join(sorted(missing_availability)[:5])
+            raise ValueError(
+                f"{len(missing_availability)} ranked questions lack full-bank p_gen "
+                f"for {generator}->{judge}/{benchmark}/{regime}: {preview}"
+            )
+
+        for (question_id, p_gen_bin_mid), values in aggregates.items():
+            records.append(
+                {
+                    "benchmark": benchmark,
+                    "question_id": question_id,
+                    "generator": generator,
+                    "judge": judge,
+                    "series_id": f"{generator}->{judge}",
+                    "p_gen": p_gen[question_id],
+                    "p_gen_bin_mid": p_gen_bin_mid,
+                    "p_correct_bin_mid": p_gen_bin_mid,
+                    **values,
+                }
+            )
+
+    frame = pd.DataFrame(records)
+    if frame.empty:
+        raise ValueError(
+            "No parse-valid selector pairs found for "
+            f"{generator}->{judge}/{regime}"
+        )
+    return frame.sort_values(["benchmark", "question_id"]).reset_index(drop=True)
+
+
+def aggregate_question_counts(question_frame: pd.DataFrame) -> pd.DataFrame:
+    question_frame = question_frame.copy()
+    if "n_parse_failed" not in question_frame.columns:
+        question_frame["n_parse_failed"] = 0
+    grouped = (
+        question_frame.groupby("p_gen_bin_mid", as_index=False)
+        .agg(
+            wins=("wins", "sum"),
+            pairs=("pairs", "sum"),
+            n_pools=("n_pools", "sum"),
+            n_parse_failed=("n_parse_failed", "sum"),
+            n_questions=("question_id", "count"),
+        )
+        .sort_values("p_gen_bin_mid")
+    )
+    grouped["auc"] = grouped["wins"] / grouped["pairs"]
+    grouped["p_correct_bin_mid"] = grouped["p_gen_bin_mid"]
+    return tag_availability_metric(grouped)
+
+
+def _question_keys(frame: pd.DataFrame) -> set[tuple[str, str]]:
+    return set(
+        zip(
+            frame["benchmark"].astype(str),
+            frame["question_id"].astype(str),
+            strict=True,
+        )
+    )
+
+
+def _filter_question_keys(
+    frame: pd.DataFrame,
+    keys: set[tuple[str, str]],
+) -> pd.DataFrame:
+    mask = [
+        (str(benchmark), str(question_id)) in keys
+        for benchmark, question_id in zip(
+            frame["benchmark"],
+            frame["question_id"],
+            strict=True,
+        )
+    ]
+    return frame.loc[mask].copy()
+
+
+def _question_overlap_row(
+    left: pd.DataFrame,
+    right: pd.DataFrame,
+    *,
+    regime: str,
+    benchmark: str,
+    left_generator: str,
+    right_generator: str,
+) -> dict[str, object]:
+    left_keys = _question_keys(left)
+    right_keys = _question_keys(right)
+    intersection = left_keys & right_keys
+    union = left_keys | right_keys
+    return {
+        "regime": regime,
+        "benchmark": benchmark,
+        "judge": "deepseek",
+        "left_generator": left_generator,
+        "right_generator": right_generator,
+        "left_questions": len(left_keys),
+        "right_questions": len(right_keys),
+        "shared_questions": len(intersection),
+        "union_questions": len(union),
+        "jaccard": len(intersection) / len(union) if union else np.nan,
+        "left_coverage": len(intersection) / len(left_keys) if left_keys else np.nan,
+        "right_coverage": len(intersection) / len(right_keys) if right_keys else np.nan,
+        "matching_unit": "benchmark and question_id",
+        "trace_pairing": "different generated traces",
+    }
+
+
+def _matched_fit_row(
+    frame: pd.DataFrame,
+    *,
+    regime: str,
+    generator: str,
+    shared_questions: int,
+) -> tuple[dict[str, object], pd.DataFrame]:
+    binned = aggregate_question_counts(frame)
+    fit = fit_boundary(binned)
+    pair_total = int(binned["pairs"].sum())
+    row = {
+        "benchmark_scope": "four_benchmark_modeling_set",
+        "regime": regime,
+        "generator": generator,
+        "judge": "deepseek",
+        "model_pair": f"{generator}->deepseek",
+        "question_support": "same benchmark-question intersection",
+        "trace_pairing": "different generated traces",
+        "n_shared_questions": shared_questions,
+        "n_pools": int(binned["n_pools"].sum()),
+        "n_pairs": pair_total,
+        "n_bins": int((binned["pairs"] > 0).sum()),
+        "mean_auc": float(binned["wins"].sum() / pair_total),
+        "A": fit["A"],
+        "slope_beta": fit["k"],
+        "midpoint": fit["midpoint"],
+        "midpoint_percent": (
+            np.nan
+            if pd.isna(fit["midpoint"])
+            else 100.0 * float(fit["midpoint"])
+        ),
+        "weighted_r2": fit["weighted_r2"],
+        "fit_status": fit["fit_status"],
+        "fit_quality": classify_fit_quality(
+            pd.to_numeric(
+                pd.Series([fit["weighted_r2"]]), errors="coerce"
+            ).iloc[0]
+        ),
+        "availability_metric": AVAILABILITY_METRIC,
+        "inference_scope": (
+            "question-matched generator-conditioned candidate distributions; "
+            "not per-trace causal effect of thinking setting"
+        ),
+    }
+    binned = binned.assign(
+        benchmark_scope="four_benchmark_modeling_set",
+        regime=regime,
+        generator=generator,
+        judge="deepseek",
+        model_pair=f"{generator}->deepseek",
+        question_support="same benchmark-question intersection",
+        trace_pairing="different generated traces",
+    )
+    return row, binned
+
+
+def _paired_generator_bootstrap(
+    left: pd.DataFrame,
+    right: pd.DataFrame,
+    *,
+    regime: str,
+    n_bootstrap: int = BOOTSTRAP_REPLICATES,
+    seed: int = BOOTSTRAP_SEED,
+) -> dict[str, object]:
+    """Resample shared questions and recompute both generator-bank fits."""
+
+    value_columns = [
+        "p_gen",
+        "p_gen_bin_mid",
+        "p_correct_bin_mid",
+        "wins",
+        "pairs",
+        "n_pools",
+        "n_parse_failed",
+    ]
+    paired = left[["benchmark", "question_id", *value_columns]].merge(
+        right[["benchmark", "question_id", *value_columns]],
+        on=["benchmark", "question_id"],
+        how="inner",
+        validate="one_to_one",
+        suffixes=("_left", "_right"),
+    )
+    if paired.empty:
+        raise ValueError(f"No shared questions for paired generator bootstrap/{regime}")
+
+    def side_frame(frame: pd.DataFrame, suffix: str) -> pd.DataFrame:
+        renamed = frame[["benchmark", "question_id"]].copy()
+        for column in value_columns:
+            renamed[column] = frame[f"{column}_{suffix}"].to_numpy()
+        return renamed
+
+    observed_left = side_frame(paired, "left")
+    observed_right = side_frame(paired, "right")
+    left_binned = aggregate_question_counts(observed_left)
+    right_binned = aggregate_question_counts(observed_right)
+    left_fit = fit_boundary(left_binned)
+    right_fit = fit_boundary(right_binned)
+    left_auc = float(left_binned["wins"].sum() / left_binned["pairs"].sum())
+    right_auc = float(right_binned["wins"].sum() / right_binned["pairs"].sum())
+
+    rng = np.random.default_rng(seed)
+    benchmark_groups = [
+        group.reset_index(drop=True)
+        for _, group in paired.groupby("benchmark", sort=True)
+    ]
+    delta_r2_samples: list[float] = []
+    delta_auc_samples: list[float] = []
+    for _ in range(n_bootstrap):
+        sampled = pd.concat(
+            [
+                group.iloc[rng.integers(0, len(group), size=len(group))]
+                for group in benchmark_groups
+            ],
+            ignore_index=True,
+        )
+        sample_left = aggregate_question_counts(side_frame(sampled, "left"))
+        sample_right = aggregate_question_counts(side_frame(sampled, "right"))
+        sample_left_fit = fit_boundary(sample_left)
+        sample_right_fit = fit_boundary(sample_right)
+        if (
+            sample_left_fit["fit_status"] != "ok"
+            or sample_right_fit["fit_status"] != "ok"
+        ):
+            continue
+        delta_r2_samples.append(
+            float(sample_right_fit["weighted_r2"])
+            - float(sample_left_fit["weighted_r2"])
+        )
+        delta_auc_samples.append(
+            float(sample_right["wins"].sum() / sample_right["pairs"].sum())
+            - float(sample_left["wins"].sum() / sample_left["pairs"].sum())
+        )
+
+    if len(delta_r2_samples) < max(100, int(0.8 * n_bootstrap)):
+        raise ValueError(
+            f"Only {len(delta_r2_samples)}/{n_bootstrap} matched bootstrap fits "
+            f"succeeded for {regime}"
+        )
+    delta_r2 = np.asarray(delta_r2_samples)
+    delta_auc = np.asarray(delta_auc_samples)
+    return {
+        "benchmark_scope": "four_benchmark_modeling_set",
+        "regime": regime,
+        "left_model_pair": "mimo->deepseek",
+        "right_model_pair": "mimo_medium->deepseek",
+        "n_shared_questions": int(len(paired)),
+        "left_mean_auc": left_auc,
+        "right_mean_auc": right_auc,
+        "delta_mean_auc": right_auc - left_auc,
+        "delta_mean_auc_ci_low": float(np.quantile(delta_auc, 0.025)),
+        "delta_mean_auc_ci_high": float(np.quantile(delta_auc, 0.975)),
+        "left_weighted_r2": float(left_fit["weighted_r2"]),
+        "right_weighted_r2": float(right_fit["weighted_r2"]),
+        "delta_weighted_r2": (
+            float(right_fit["weighted_r2"]) - float(left_fit["weighted_r2"])
+        ),
+        "delta_weighted_r2_ci_low": float(np.quantile(delta_r2, 0.025)),
+        "delta_weighted_r2_ci_high": float(np.quantile(delta_r2, 0.975)),
+        "n_bootstrap": n_bootstrap,
+        "n_bootstrap_success": len(delta_r2_samples),
+        "bootstrap_unit": "paired question, stratified by benchmark",
+        "bootstrap_seed": seed,
+        "question_support": "same benchmark-question intersection",
+        "trace_pairing": "different generated traces",
+        "inference_scope": (
+            "question-matched generator-conditioned candidate distributions; "
+            "not per-trace causal effect of thinking setting"
+        ),
+    }
+
+
+def build_generator_bank_question_matched_summaries(
+    formal_root: Path = FIVE_BENCH_ROOT,
+    benchmarks: Iterable[str] = MODELING_BENCHMARKS,
+    *,
+    sample_bank_dirs: Mapping[str, Path] | None = None,
+) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
+    """Quantify support overlap and refit generator contrasts on the same questions."""
+
+    resolved_benchmarks = tuple(benchmarks)
+    sample_dirs = SAMPLE_BANK_DIR_OVERRIDES if sample_bank_dirs is None else sample_bank_dirs
+    overlap_rows: list[dict[str, object]] = []
+    fit_rows: list[dict[str, object]] = []
+    binned_frames: list[pd.DataFrame] = []
+    bootstrap_rows: list[dict[str, object]] = []
+
+    for regime in ("natural", "balanced"):
+        frames = {
+            generator: question_level_selector_counts(
+                formal_root,
+                resolved_benchmarks,
+                regime,
+                generator=generator,
+                judge="deepseek",
+                sample_bank_dirs=sample_dirs,
+            ).query("pairs > 0").copy()
+            for generator in ("deepseek", "mimo", "mimo_medium")
+        }
+
+        for left_generator, right_generator in (
+            ("deepseek", "mimo"),
+            ("deepseek", "mimo_medium"),
+            ("mimo", "mimo_medium"),
+        ):
+            for benchmark in (*resolved_benchmarks, "__pooled__"):
+                left = frames[left_generator]
+                right = frames[right_generator]
+                if benchmark != "__pooled__":
+                    left = left[left["benchmark"] == benchmark]
+                    right = right[right["benchmark"] == benchmark]
+                overlap_rows.append(
+                    _question_overlap_row(
+                        left,
+                        right,
+                        regime=regime,
+                        benchmark=benchmark,
+                        left_generator=left_generator,
+                        right_generator=right_generator,
+                    )
+                )
+
+        left = frames["mimo"]
+        right = frames["mimo_medium"]
+        shared_keys = _question_keys(left) & _question_keys(right)
+        matched_left = _filter_question_keys(left, shared_keys)
+        matched_right = _filter_question_keys(right, shared_keys)
+        for generator, frame in (("mimo", left), ("mimo_medium", right)):
+            matched = matched_left if generator == "mimo" else matched_right
+            row, binned = _matched_fit_row(
+                matched,
+                regime=regime,
+                generator=generator,
+                shared_questions=len(shared_keys),
+            )
+            fit_rows.append(row)
+            binned_frames.append(binned)
+        bootstrap_rows.append(
+            _paired_generator_bootstrap(
+                matched_left,
+                matched_right,
+                regime=regime,
+            )
+        )
+
+    overlap = pd.DataFrame(overlap_rows)
+    fits = pd.DataFrame(fit_rows)
+    binned = pd.concat(binned_frames, ignore_index=True)
+    bootstrap = pd.DataFrame(bootstrap_rows)
+    overlap.to_csv(
+        OUT_DIR / "selector_boundary_generator_bank_question_overlap.csv",
+        index=False,
+    )
+    fits.to_csv(
+        OUT_DIR / "selector_boundary_generator_bank_matched_fit_summary.csv",
+        index=False,
+    )
+    binned.to_csv(
+        OUT_DIR / "selector_boundary_generator_bank_matched_binned_auc.csv",
+        index=False,
+    )
+    bootstrap.to_csv(
+        OUT_DIR / "selector_boundary_generator_bank_matched_bootstrap_summary.csv",
+        index=False,
+    )
+    return overlap, fits, binned
+
+
+def bootstrap_selector_scope(
+    question_frame: pd.DataFrame,
+    benchmark_scope: str,
+    regime: str,
+    *,
+    n_bootstrap: int = BOOTSTRAP_REPLICATES,
+    seed: int = BOOTSTRAP_SEED,
+) -> tuple[dict[str, object], pd.DataFrame, pd.DataFrame]:
+    """Bootstrap questions within benchmark strata and refit the boundary."""
+
+    observed = aggregate_question_counts(question_frame)
+    observed_fit = fit_boundary(observed)
+    if observed_fit["fit_status"] != "ok":
+        raise ValueError(f"Observed boundary fit failed for {benchmark_scope}/{regime}")
+
+    rng = np.random.default_rng(seed)
+    benchmark_groups = [group.reset_index(drop=True) for _, group in question_frame.groupby("benchmark", sort=True)]
+    bins = observed["p_gen_bin_mid"].to_numpy(dtype=float)
+    grid = np.linspace(0.002, 0.998, 250)
+    midpoint_samples: list[float] = []
+    curve_samples: list[np.ndarray] = []
+    auc_samples: dict[float, list[float]] = {float(value): [] for value in bins}
+
+    for _ in range(n_bootstrap):
+        sampled = pd.concat(
+            [group.iloc[rng.integers(0, len(group), size=len(group))] for group in benchmark_groups],
+            ignore_index=True,
+        )
+        binned = aggregate_question_counts(sampled)
+        auc_by_bin = binned.set_index("p_gen_bin_mid")["auc"].to_dict()
+        for value in bins:
+            auc_samples[float(value)].append(float(auc_by_bin.get(float(value), np.nan)))
+
+        fit = fit_boundary(binned)
+        if fit["fit_status"] != "ok":
+            continue
+        midpoint_samples.append(float(fit["midpoint"]))
+        curve_samples.append(
+            auc_boundary(grid, float(fit["A"]), float(fit["k"]), float(fit["midpoint"]))
+        )
+
+    if len(midpoint_samples) < max(100, int(0.8 * n_bootstrap)):
+        raise ValueError(
+            f"Only {len(midpoint_samples)}/{n_bootstrap} bootstrap fits succeeded for {benchmark_scope}/{regime}"
+        )
+
+    midpoint_array = np.asarray(midpoint_samples)
+    curve_array = np.vstack(curve_samples)
+    summary = {
+        "benchmark_scope": benchmark_scope,
+        "regime": regime,
+        "availability_metric": AVAILABILITY_METRIC,
+        "availability_definition": AVAILABILITY_DEFINITION,
+        "midpoint_definition": MIDPOINT_DEFINITION,
+        "observed_midpoint": float(observed_fit["midpoint"]),
+        "midpoint_ci_low": float(np.quantile(midpoint_array, 0.025)),
+        "midpoint_ci_high": float(np.quantile(midpoint_array, 0.975)),
+        "n_questions": int(len(question_frame)),
+        "n_pools": int(question_frame["n_pools"].sum()),
+        "n_pairs": int(question_frame["pairs"].sum()),
+        "n_bootstrap": n_bootstrap,
+        "n_bootstrap_success": int(len(midpoint_samples)),
+        "bootstrap_unit": "question, stratified by benchmark",
+        "bootstrap_seed": seed,
+    }
+
+    binned_rows: list[dict[str, object]] = []
+    for row in observed.itertuples(index=False):
+        samples = np.asarray(auc_samples[float(row.p_gen_bin_mid)], dtype=float)
+        finite = samples[np.isfinite(samples)]
+        binned_rows.append(
+            {
+                "benchmark_scope": benchmark_scope,
+                "regime": regime,
+                "p_gen_bin_mid": row.p_gen_bin_mid,
+                "auc": row.auc,
+                "auc_ci_low": float(np.quantile(finite, 0.025)),
+                "auc_ci_high": float(np.quantile(finite, 0.975)),
+                "wins": row.wins,
+                "pairs": row.pairs,
+                "n_pools": row.n_pools,
+                "n_questions": row.n_questions,
+                "availability_metric": AVAILABILITY_METRIC,
+            }
+        )
+
+    curve = pd.DataFrame(
+        {
+            "benchmark_scope": benchmark_scope,
+            "regime": regime,
+            "p_gen": grid,
+            "fit_auc": auc_boundary(
+                grid,
+                float(observed_fit["A"]),
+                float(observed_fit["k"]),
+                float(observed_fit["midpoint"]),
+            ),
+            "fit_ci_low": np.quantile(curve_array, 0.025, axis=0),
+            "fit_ci_high": np.quantile(curve_array, 0.975, axis=0),
+            "availability_metric": AVAILABILITY_METRIC,
+        }
+    )
+    return summary, pd.DataFrame(binned_rows), curve
+
+
+def build_selector_boundary_bootstrap_summaries() -> None:
+    specs = [
+        (
+            FIVE_BENCH_ROOT,
+            ("mmlu_pro", "gpqa", "medxpertqa", "musr"),
+            "four_benchmark_modeling_set",
+            "natural",
+        ),
+        (
+            FIVE_BENCH_ROOT,
+            ("mmlu_pro", "gpqa", "medxpertqa", "musr"),
+            "four_benchmark_modeling_set",
+            "balanced",
+        ),
+        (FIVE_BENCH_ROOT, ("hle_text_mc",), "hle_mc_external_validation", "natural"),
+        (HLE_QA_ROOT, ("hle_text_qa_verified",), "hle_qa_open_answer_diagnostic", "natural"),
+    ]
+    summaries: list[dict[str, object]] = []
+    binned_frames: list[pd.DataFrame] = []
+    curve_frames: list[pd.DataFrame] = []
+    for formal_root, benchmarks, benchmark_scope, regime in specs:
+        question_frame = question_level_selector_counts(formal_root, benchmarks, regime)
+        summary, binned, curve = bootstrap_selector_scope(
+            question_frame,
+            benchmark_scope,
+            regime,
+        )
+        summaries.append(summary)
+        binned_frames.append(binned)
+        curve_frames.append(curve)
+
+    pd.DataFrame(summaries).to_csv(OUT_DIR / "selector_boundary_question_bootstrap_summary.csv", index=False)
+    pd.concat(binned_frames, ignore_index=True).to_csv(
+        OUT_DIR / "selector_boundary_binned_auc_question_ci.csv",
+        index=False,
+    )
+    pd.concat(curve_frames, ignore_index=True).to_csv(
+        OUT_DIR / "selector_boundary_curve_question_ci.csv",
+        index=False,
+    )
+
+
+def build_selector_boundary_summaries() -> None:
+    model_binned, _model_fits = build_model_pair_boundary_summaries()
+    four = model_binned[
+        (model_binned["benchmark_scope"] == "four_benchmark_modeling_set")
+        & np.isclose(model_binned["bin_width"], 0.02)
+    ].copy()
+    hle_qa = tag_availability_metric(pd.read_csv(HLE_QA_MODEL_PAIR_BINNED))
+    hle_qa["benchmark"] = "hle_text_qa_verified"
+    hle_mc = model_binned[
+        (model_binned["benchmark_scope"] == "hle_text_mc")
+        & np.isclose(model_binned["bin_width"], 0.02)
+    ].copy()
+    validate_availability_frame(four, "four-benchmark boundary")
+    validate_availability_frame(hle_mc, "HLE MC boundary")
+    validate_availability_frame(hle_qa, "HLE QA boundary")
+    hle_mc.to_csv(OUT_DIR / "hle_mc_model_pair_binned_auc.csv", index=False)
+
+    all_rows: list[dict[str, object]] = []
+    all_rows += add_fit_rows(
+        four,
+        "four_benchmark_modeling_set",
+        "MMLU-Pro + GPQA + MedXpertQA + MuSR",
+        OUT_DIR / "selector_boundary_model_pair_binned_auc.csv",
+        "official benchmark answer keys",
+        "main_boundary",
+        "Main text should use DS-DS as the clean primary line; other model pairs are robustness.",
+    )
+    all_rows += add_fit_rows(
+        hle_mc,
+        "hle_mc_external_validation",
+        "HLE multiple-choice",
+        OUT_DIR / "hle_mc_model_pair_binned_auc.csv",
+        "official multiple-choice labels",
+        "external_validation",
+        "HLE MC was not used to fit the four-benchmark boundary.",
+    )
+    all_rows += add_fit_rows(
+        hle_qa,
+        "hle_qa_open_answer_diagnostic",
+        "HLE open-answer QA",
+        HLE_QA_MODEL_PAIR_BINNED,
+        "DeepSeek reference-answer equivalence judge plus HLE reference answers",
+        "judge_dependent_external_diagnostic",
+        "Open-answer correctness labels are judge-dependent; ranking judge did not receive the reference answer.",
+    )
+    fits = pd.DataFrame(all_rows)
+    order = {pair_id: index for index, pair_id in enumerate(MODEL_PAIR_IDS)}
+    fits["_pair_order"] = fits["model_pair"].map(order).fillna(99)
+    fits = fits.sort_values(["benchmark_scope", "regime", "_pair_order"]).drop(columns=["_pair_order"])
+    fits.to_csv(OUT_DIR / "selector_boundary_2x2_robustness_summary.csv", index=False)
+
+    dsds = fits[fits["model_pair"] == "deepseek->deepseek"].copy()
+    dsds["primary_fig2_use"] = np.where(dsds["regime"] == "natural", "main_fig2_boundary_or_external_shift", "balanced_diagnostic")
+    dsds.to_csv(OUT_DIR / "selector_boundary_dsds_fit_summary.csv", index=False)
+
+    binned_dsds = pd.concat(
+        [
+            four[four["series_id"] == "deepseek->deepseek"].assign(benchmark_scope="four_benchmark_modeling_set"),
+            hle_mc[hle_mc["series_id"] == "deepseek->deepseek"].assign(benchmark_scope="hle_mc_external_validation"),
+            hle_qa[hle_qa["series_id"] == "deepseek->deepseek"].assign(benchmark_scope="hle_qa_open_answer_diagnostic"),
+        ],
+        ignore_index=True,
+    )
+    binned_dsds.to_csv(OUT_DIR / "selector_boundary_dsds_binned_auc.csv", index=False)
+    build_selector_boundary_bootstrap_summaries()
+
+
+def build_replay_summaries() -> None:
+    bench = pd.read_csv(GLOBAL_REPLAY_ROOT / "benchmark_summary.csv")
+    bench["benchmark_label"] = bench["benchmark"].map(BENCHMARK_LABELS).fillna(bench["benchmark"])
+    bench["strategy_label"] = bench["strategy"].map(STRATEGY_LABELS).fillna(bench["strategy"])
+    bench["regime"] = "natural"
+    bench["generator"] = "deepseek"
+    bench["judge"] = "deepseek"
+    bench["accuracy_percent"] = bench["accuracy"] * 100.0
+    bench["ci_low_percent"] = bench["ci_low"] * 100.0
+    bench["ci_high_percent"] = bench["ci_high"] * 100.0
+    bench["source_file"] = rel(GLOBAL_REPLAY_ROOT / "benchmark_summary.csv")
+    bench.to_csv(OUT_DIR / "natural_replay_accuracy_summary.csv", index=False)
+
+    paired = pd.read_csv(GLOBAL_REPLAY_ROOT / "paired_deltas.csv")
+    paired["benchmark_label"] = paired["benchmark"].map(BENCHMARK_LABELS).fillna(paired["benchmark"])
+    paired["regime"] = "natural"
+    paired["generator"] = "deepseek"
+    paired["judge"] = "deepseek"
+    paired["mean_delta_percent_points"] = paired["mean_delta"] * 100.0
+    paired["ci_low_percent_points"] = paired["ci_low"] * 100.0
+    paired["ci_high_percent_points"] = paired["ci_high"] * 100.0
+    paired["source_file"] = rel(GLOBAL_REPLAY_ROOT / "paired_deltas.csv")
+    paired.to_csv(OUT_DIR / "natural_replay_paired_delta_summary.csv", index=False)
+
+    strat = pd.read_csv(GLOBAL_REPLAY_ROOT / "stratified_summary.csv")
+    strat["benchmark_label"] = strat["benchmark"].map(BENCHMARK_LABELS).fillna(strat["benchmark"])
+    strat["strategy_label"] = strat["strategy"].map(STRATEGY_LABELS).fillna(strat["strategy"])
+    strat["regime"] = "natural"
+    strat["generator"] = "deepseek"
+    strat["judge"] = "deepseek"
+    strat["accuracy_percent"] = strat["accuracy"] * 100.0
+    strat["ci_low_percent"] = strat["ci_low"] * 100.0
+    strat["ci_high_percent"] = strat["ci_high"] * 100.0
+    strat["source_file"] = rel(GLOBAL_REPLAY_ROOT / "stratified_summary.csv")
+    strat.to_csv(OUT_DIR / "natural_replay_stratified_summary.csv", index=False)
+
+
+def build_mechanism_summaries() -> None:
+    minority = pd.read_csv(MINORITY_ROOT / "selector_delta_bootstrap_ci.csv")
+    for prefix in ("rank_soft", "shuffled", "rank_minus_shuffled"):
+        minority[f"{prefix}_mean_delta_pp"] = minority[f"{prefix}_mean" if prefix == "rank_minus_shuffled" else f"{prefix}_mean_delta"] * 100.0
+    minority["rank_soft_ci_low_pp"] = minority["rank_soft_ci_low"] * 100.0
+    minority["rank_soft_ci_high_pp"] = minority["rank_soft_ci_high"] * 100.0
+    minority["shuffled_ci_low_pp"] = minority["shuffled_ci_low"] * 100.0
+    minority["shuffled_ci_high_pp"] = minority["shuffled_ci_high"] * 100.0
+    minority["rank_soft_ci_excludes_zero"] = (minority["rank_soft_ci_low"] > 0) | (minority["rank_soft_ci_high"] < 0)
+    minority["shuffled_ci_excludes_zero"] = (minority["shuffled_ci_low"] > 0) | (minority["shuffled_ci_high"] < 0)
+    minority["manuscript_role"] = "false_majority_mechanism_control"
+    minority["source_file"] = rel(MINORITY_ROOT / "selector_delta_bootstrap_ci.csv")
+    minority.to_csv(OUT_DIR / "minority_diffusion_mechanism_summary.csv", index=False)
+
+    perturb = pd.read_csv(PERTURB_ROOT / "llm_rerank_analysis" / "summary.csv")
+    perturb["rank_auc_percent"] = perturb["rank_auc"] * 100.0
+    perturb["top1_correct_percent"] = perturb["top1_correct_rate"] * 100.0
+    perturb["top2_correct_percent"] = perturb["top2_correct_rate"] * 100.0
+    perturb["parse_ok_rate"] = perturb["n_parse_ok"] / perturb["n_rows"]
+    perturb["source_file"] = rel(PERTURB_ROOT / "llm_rerank_analysis" / "summary.csv")
+    perturb.to_csv(OUT_DIR / "perturbation_prompt_mode_summary.csv", index=False)
+
+
+def _load_k16_cohort_strategy_rows(
+    cohort: str,
+    spec: Mapping[str, object],
+) -> pd.DataFrame:
+    """Recompute k=16 majority, rank and oracle outcomes from preserved rows."""
+
+    pools_path = Path(spec["pools"])
+    rankings_path = Path(spec["rankings"])
+    generator = str(spec["generator"])
+    pools = pd.read_csv(pools_path, dtype=str, keep_default_na=False)
+    rankings = pd.read_csv(rankings_path, dtype=str, keep_default_na=False)
+    if "generator" in pools.columns:
+        pools = pools[pools["generator"] == generator].copy()
+    if "generator" in rankings.columns:
+        rankings = rankings[rankings["generator"] == generator].copy()
+    rankings = rankings[
+        rankings["parse_ok"].astype(str).str.strip().str.lower().isin(TRUTHY)
+    ].copy()
+    if rankings["pool_id"].duplicated().any():
+        raise ValueError(f"Duplicate parse-valid k=16 rankings in {cohort}")
+    ranking_by_pool = rankings.set_index("pool_id", drop=False).to_dict("index")
+
+    rows: list[dict[str, object]] = []
+    for pool_id, group in pools.groupby("pool_id", sort=False):
+        ranking_row = ranking_by_pool.get(str(pool_id))
+        if ranking_row is None or len(group) != 16:
+            continue
+        ordered = group.copy()
+        ordered["_sample_index"] = pd.to_numeric(
+            ordered["sample_index"], errors="raise"
+        )
+        ordered = ordered.sort_values("_sample_index", kind="stable")
+        pool_rows = ordered.drop(columns="_sample_index").to_dict("records")
+        key = {
+            "benchmark": str(ordered.iloc[0]["benchmark"]),
+            "question_id": str(ordered.iloc[0]["question_id"]),
+        }
+        rows.append(
+            {
+                **key,
+                "cohort": cohort,
+                "generator": generator,
+                "pool_id": str(pool_id),
+                "majority_vote_correct": int(
+                    _strategy_correct(
+                        pool_rows,
+                        ranking_row,
+                        "majority@16",
+                        K16_STRATEGY_SEED,
+                    )
+                ),
+                "deepseek_rank_correct": int(
+                    _strategy_correct(
+                        pool_rows,
+                        ranking_row,
+                        "rank@16",
+                        K16_STRATEGY_SEED,
+                    )
+                ),
+                "oracle_correct": int(
+                    _strategy_correct(
+                        pool_rows,
+                        ranking_row,
+                        "oracle@16",
+                        K16_STRATEGY_SEED,
+                    )
+                ),
+                "pools_source": rel(pools_path),
+                "rankings_source": rel(rankings_path),
+            }
+        )
+    frame = pd.DataFrame(rows)
+    if frame.empty:
+        raise ValueError(f"No complete parse-valid k=16 rows found for {cohort}")
+    key_columns = ["benchmark", "question_id"]
+    if frame.duplicated(key_columns).any():
+        raise ValueError(f"Multiple k=16 pools per benchmark-question in {cohort}")
+    return frame
+
+
+def build_k16_question_matched_pool_setting_summary(
+    *,
+    n_bootstrap: int = BOOTSTRAP_REPLICATES,
+    seed: int = BOOTSTRAP_SEED,
+) -> tuple[pd.DataFrame, pd.DataFrame]:
+    """Compare Mimo pool settings on exactly the same k=16 questions."""
+
+    frames = {
+        cohort: _load_k16_cohort_strategy_rows(cohort, spec)
+        for cohort, spec in K16_MATCHED_COHORTS.items()
+    }
+    no_think = frames["mimo_no_think"]
+    medium = frames["mimo_medium_thinking"]
+    keys = ["benchmark", "question_id"]
+    paired = no_think.merge(
+        medium,
+        on=keys,
+        how="inner",
+        validate="one_to_one",
+        suffixes=("_no_think", "_medium"),
+    )
+    if paired.empty:
+        raise ValueError("No shared k=16 questions across Mimo pool settings")
+
+    metric_columns = (
+        "majority_vote_correct",
+        "deepseek_rank_correct",
+        "oracle_correct",
+    )
+    observed: dict[str, dict[str, float]] = {}
+    for suffix, cohort in (
+        ("no_think", "mimo_no_think"),
+        ("medium", "mimo_medium_thinking"),
+    ):
+        values = {
+            metric: float(paired[f"{metric}_{suffix}"].mean())
+            for metric in metric_columns
+        }
+        values["rank_minus_majority"] = (
+            values["deepseek_rank_correct"] - values["majority_vote_correct"]
+        )
+        observed[cohort] = values
+
+    rng = np.random.default_rng(seed)
+    benchmark_groups = [
+        group.reset_index(drop=True)
+        for _, group in paired.groupby("benchmark", sort=True)
+    ]
+    bootstrap_values: dict[str, list[float]] = defaultdict(list)
+    for _ in range(n_bootstrap):
+        sampled = pd.concat(
+            [
+                group.iloc[rng.integers(0, len(group), size=len(group))]
+                for group in benchmark_groups
+            ],
+            ignore_index=True,
+        )
+        for suffix, cohort in (
+            ("no_think", "mimo_no_think"),
+            ("medium", "mimo_medium_thinking"),
+        ):
+            majority = float(sampled[f"majority_vote_correct_{suffix}"].mean())
+            rank = float(sampled[f"deepseek_rank_correct_{suffix}"].mean())
+            bootstrap_values[f"{cohort}:rank_minus_majority"].append(rank - majority)
+        for metric in metric_columns:
+            bootstrap_values[f"contrast:{metric}"].append(
+                float(sampled[f"{metric}_medium"].mean())
+                - float(sampled[f"{metric}_no_think"].mean())
+            )
+        bootstrap_values["contrast:rank_minus_majority"].append(
+            bootstrap_values["mimo_medium_thinking:rank_minus_majority"][-1]
+            - bootstrap_values["mimo_no_think:rank_minus_majority"][-1]
+        )
+
+    summary_rows: list[dict[str, object]] = []
+    for cohort, frame in frames.items():
+        values = observed[cohort]
+        gains = np.asarray(bootstrap_values[f"{cohort}:rank_minus_majority"])
+        summary_rows.append(
+            {
+                "cohort": cohort,
+                "generator": str(K16_MATCHED_COHORTS[cohort]["generator"]),
+                "ranking_judge": "deepseek",
+                "pool_size": 16,
+                "n_source_questions": int(len(frame)),
+                "n_shared_questions": int(len(paired)),
+                "shared_question_coverage": float(len(paired) / len(frame)),
+                "majority_vote_accuracy": values["majority_vote_correct"],
+                "deepseek_rank_accuracy": values["deepseek_rank_correct"],
+                "oracle_accuracy": values["oracle_correct"],
+                "rank_minus_majority_pp": values["rank_minus_majority"] * 100.0,
+                "rank_minus_majority_ci_low_pp": float(np.quantile(gains, 0.025) * 100.0),
+                "rank_minus_majority_ci_high_pp": float(np.quantile(gains, 0.975) * 100.0),
+                "n_bootstrap": n_bootstrap,
+                "bootstrap_unit": "paired question, stratified by benchmark",
+                "bootstrap_seed": seed,
+                "question_support": "exact benchmark-question intersection",
+                "trace_pairing": "different generated traces",
+            }
+        )
+
+    contrast_row: dict[str, object] = {
+        "contrast": "mimo_medium_thinking_minus_mimo_no_think",
+        "pool_size": 16,
+        "n_shared_questions": int(len(paired)),
+        "n_bootstrap": n_bootstrap,
+        "bootstrap_unit": "paired question, stratified by benchmark",
+        "bootstrap_seed": seed,
+        "question_support": "exact benchmark-question intersection",
+        "trace_pairing": "different generated traces",
+        "inference_scope": (
+            "question-matched generator-conditioned pool distributions; "
+            "not a per-trace causal effect of thinking setting"
+        ),
+    }
+    for metric in (*metric_columns, "rank_minus_majority"):
+        observed_delta = (
+            observed["mimo_medium_thinking"][metric]
+            - observed["mimo_no_think"][metric]
+        )
+        samples = np.asarray(bootstrap_values[f"contrast:{metric}"])
+        prefix = metric.removesuffix("_correct")
+        contrast_row[f"delta_{prefix}_pp"] = observed_delta * 100.0
+        contrast_row[f"delta_{prefix}_ci_low_pp"] = float(
+            np.quantile(samples, 0.025) * 100.0
+        )
+        contrast_row[f"delta_{prefix}_ci_high_pp"] = float(
+            np.quantile(samples, 0.975) * 100.0
+        )
+
+    summary = pd.DataFrame(summary_rows)
+    contrast = pd.DataFrame([contrast_row])
+    summary.to_csv(
+        OUT_DIR / "pool_setting_k16_question_matched_strategy_summary.csv",
+        index=False,
+    )
+    contrast.to_csv(
+        OUT_DIR / "pool_setting_k16_question_matched_contrast.csv",
+        index=False,
+    )
+    return summary, contrast
+
+
+def build_pool_size_cost_summary() -> None:
+    cost = pd.read_csv(POOL_COST_ROOT / "summaries" / "natural_pool_size_strategy_accuracy_cost.csv")
+    cost = cost[(cost["benchmark"] == "__global__") & (cost["cost_scenario"] == "paid_equivalent_cache_miss")].copy()
+    cost["regime"] = "natural"
+    cost["method_family"] = cost["strategy"].str.extract(r"^([^@]+)", expand=False)
+    cost["accuracy_percent"] = cost["accuracy"] * 100.0
+    cost["ci_low_percent"] = cost["ci_low"] * 100.0
+    cost["ci_high_percent"] = cost["ci_high"] * 100.0
+    cost["source_file"] = rel(POOL_COST_ROOT / "summaries" / "natural_pool_size_strategy_accuracy_cost.csv")
+    keep = [
+        "population",
+        "regime",
+        "pool_size",
+        "rank_source",
+        "benchmark",
+        "generator",
+        "selector",
+        "cell_id",
+        "strategy",
+        "method_family",
+        "cost_scenario",
+        "n_questions",
+        "accuracy",
+        "accuracy_percent",
+        "ci_low_percent",
+        "ci_high_percent",
+        "generation_requests",
+        "selector_requests",
+        "total_tokens",
+        "estimated_cost_usd_normalized",
+        "relative_cost_vs_single",
+        "cost_per_correct",
+        "accuracy_status",
+        "source_file",
+    ]
+    cost[keep].to_csv(OUT_DIR / "pool_size_cost_summary.csv", index=False)
+
+
+def markdown_table(rows: Iterable[Iterable[object]], headers: list[str]) -> str:
+    out = ["| " + " | ".join(headers) + " |", "| " + " | ".join(["---"] * len(headers)) + " |"]
+    for row in rows:
+        out.append("| " + " | ".join(str(x) for x in row) + " |")
+    return "\n".join(out)
+
+
+def write_readme_and_index() -> None:
+    dsds = pd.read_csv(OUT_DIR / "selector_boundary_dsds_fit_summary.csv")
+    replay = pd.read_csv(OUT_DIR / "natural_replay_accuracy_summary.csv")
+    paired = pd.read_csv(OUT_DIR / "natural_replay_paired_delta_summary.csv")
+    minority = pd.read_csv(OUT_DIR / "minority_diffusion_mechanism_summary.csv")
+
+    main_boundary = dsds[(dsds["benchmark_scope"] == "four_benchmark_modeling_set") & (dsds["regime"] == "natural")].iloc[0]
+    replay_global = replay[(replay["benchmark"] == "__global__") & (replay["strategy"] == "rank_soft_copy")].iloc[0]
+    replay_majority = replay[(replay["benchmark"] == "__global__") & (replay["strategy"] == "majority_vote")].iloc[0]
+    replay_delta = paired[(paired["benchmark"] == "__global__") & (paired["stratum"] == "__all__") & (paired["contrast"] == "rank_soft_copy_minus_majority_vote")].iloc[0]
+
+    readme = f"""# Manuscript-Facing Formal Derived Summaries
+
+These files are derived, manuscript-facing summaries built from the immutable
+formal evidence packages under `results/formal/`. They clarify naming, regime,
+model-pair, label-source and manuscript role without renaming or moving the
+original formal artifacts.
+
+## Generated Tables
+
+{markdown_table(
+        [
+            ["selector_boundary_dsds_fit_summary.csv", "Fig. 2 main DS-DS boundary and external validation"],
+            ["selector_boundary_dsds_binned_auc.csv", "Fig. 2 DS-DS binned AUC source data"],
+            ["selector_boundary_model_pair_binned_auc.csv", "Seven-cell benchmark-resolved generator-judge sensitivity"],
+            ["selector_boundary_model_pair_fit_summary.csv", "Seven-cell pooled four- and five-benchmark boundary fits"],
+            ["selector_boundary_medium_sensitivity_summary.csv", "Matched-factor Mimo no-think-versus-medium sensitivity contrasts"],
+            ["selector_boundary_generator_bank_question_overlap.csv", "Benchmark-question overlap across generator banks under the same DeepSeek judge"],
+            ["selector_boundary_generator_bank_matched_fit_summary.csv", "Generator-bank boundary fits restricted to the exact shared-question support"],
+            ["selector_boundary_generator_bank_matched_binned_auc.csv", "Binned AUC evidence for the shared-question generator-bank fits"],
+            ["selector_boundary_generator_bank_matched_bootstrap_summary.csv", "Paired question-bootstrap intervals for the shared-support generator contrast"],
+            ["selector_boundary_model_pair_source_manifest.csv", "Source paths, hashes, parse coverage and sample-bank provenance"],
+            ["selector_boundary_2x2_robustness_summary.csv", "Legacy-compatible four-cell generator-selector summary"],
+            ["hle_mc_model_pair_binned_auc.csv", "Derived HLE MC model-pair binned AUC from formal pools and rankings"],
+            ["natural_replay_accuracy_summary.csv", "Fig. 3 natural-pool replay accuracy"],
+            ["natural_replay_paired_delta_summary.csv", "Fig. 3 paired replay contrasts"],
+            ["natural_replay_stratified_summary.csv", "Fig. 3 p_correct regime stratification"],
+            ["minority_diffusion_mechanism_summary.csv", "Fig. 4 false-majority mechanism summary"],
+            ["perturbation_prompt_mode_summary.csv", "Fig. 4 prompt-information perturbation summary"],
+            ["pool_size_cost_summary.csv", "Fig. 4 natural pool-size and cost summary"],
+            ["pool_setting_k16_question_matched_strategy_summary.csv", "ED Fig. 6 k=16 strategy outcomes on exact shared question support"],
+            ["pool_setting_k16_question_matched_contrast.csv", "Paired question-bootstrap contrast between Mimo no-think and medium-thinking k=16 pools"],
+        ],
+        ["File", "Manuscript role"],
+    )}
+
+## Headline Checks
+
+- Four-benchmark DS-DS natural boundary midpoint:
+  `{main_boundary['midpoint_percent']:.2f}%`, weighted R2 `{main_boundary['weighted_r2']:.4f}`.
+- Complete natural-pool replay rank-guided accuracy:
+  `{replay_global['accuracy_percent']:.2f}%`.
+- Complete natural-pool replay majority-vote accuracy:
+  `{replay_majority['accuracy_percent']:.2f}%`.
+- Rank-guided minus majority paired delta:
+  `{replay_delta['mean_delta_percent_points']:.2f} pp`
+  with 95% CI [`{replay_delta['ci_low_percent_points']:.2f}`, `{replay_delta['ci_high_percent_points']:.2f}`].
+- Minority-correct mechanism cells:
+  `{int((minority['rank_soft_mean_delta'] > 0).sum())}/{len(minority)}` have positive rank-soft mean delta.
+
+## Mimo-Medium Provenance And Pilot Reconciliation
+
+- The four `selector_boundary_model_pair_*.csv` and sensitivity files in this
+  directory supersede
+  `results/pilots/medium_thinking_selector_boundary/analysis/formal_mimo_medium_vs_original_mimo_fit_point_estimates.csv`
+  for manuscript use.
+- The canonical analysis uses exactly seven observed generator-judge cells; it
+  does not impute the two unrun Mimo-no-think/Mimo-medium cross-cells.
+- For the two pooled four-benchmark curves generated by Mimo (no-think), pair
+  counts and pair-weighted mean AUC agree with the pilot snapshot, but the
+  reported weighted R2 differs because these nearly flat curves hit the fitted
+  amplitude bound (canonical `A <= 0.55`; pilot `A <= 0.60`). Both versions are
+  classified as low-R2 diagnostics, so midpoint and R2 differences in these two
+  cells are not interpreted as substantive changes.
+- An incremental run status such as `skipped_no_tasks` means that the runner
+  found no missing work; source presence and parse coverage are established
+  independently by `selector_boundary_model_pair_source_manifest.csv`.
+
+## Regime Naming
+
+- `natural`: candidate pools preserve the observed correct/wrong prevalence from stochastic generation.
+- `balanced`: candidate pools are controlled diagnostic/stress-test pools and should not be described as real task prevalence.
+- `DS-DS`: DeepSeek-generated candidates ranked by DeepSeek judge. This is the clean main text line for Fig. 2 and Fig. 3.
+- `seven-cell model-pair sensitivity`: the four original DeepSeek/Mimo-no-think cells plus DS-generated/Mimo-medium-judged, Mimo-medium-generated/DS-judged and Mimo-medium self-judged cells. The two unrun Mimo-no-think/Mimo-medium cross-cells are not imputed.
+- `Mimo (no-think)` and `Mimo (medium-thinking)` are distinct generator or judge conditions. Medium-thinking candidate availability is computed from its own tracked sample bank, never from the Mimo-no-think bank.
+- Cross-model cells are robustness and sensitivity evidence. The manuscript's primary boundary remains the pre-specified DS-DS four-benchmark natural line.
+"""
+    (OUT_DIR / "README.md").write_text(readme, encoding="utf-8")
+
+    index = """# Formal Evidence Index
+
+This index names the formal evidence in manuscript language. The original
+`results/formal/` packages remain the provenance source; this index points to
+derived summaries intended for figures, tables and reviewer-facing claims.
+
+## Evidence Map
+
+"""
+    index += markdown_table(
+        [
+            [
+                "Selector availability boundary",
+                "Main mechanism law",
+                "Four-benchmark DS-DS natural/balanced",
+                "official answer keys",
+                "Fig. 2B/E",
+                "derived_summaries/selector_boundary_dsds_fit_summary.csv",
+            ],
+            [
+                "HLE external boundary shift",
+                "External validation / stress test",
+                "HLE MC and HLE QA DS-DS natural",
+                "HLE MC official labels; HLE QA DeepSeek reference-equivalence labels",
+                "Fig. 2C/D",
+                "derived_summaries/selector_boundary_dsds_fit_summary.csv",
+            ],
+            [
+                "Seven-cell selector sensitivity",
+                "Cross-model sensitivity",
+                "Four original cells plus three observed Mimo-medium cells; no imputation of the two unrun cross-cells",
+                "same as each benchmark family",
+                "Fig. 2D, Extended Data and Supplement",
+                "derived_summaries/selector_boundary_model_pair_fit_summary.csv",
+            ],
+            [
+                "Question-matched generator sensitivity",
+                "Matched-support robustness",
+                "Same benchmark-question intersection for Mimo no-think and Mimo medium-thinking banks under the DeepSeek judge",
+                "official benchmark answer keys",
+                "Fig. 2D and Methods",
+                "derived_summaries/selector_boundary_generator_bank_matched_fit_summary.csv",
+            ],
+            [
+                "Complete natural-pool replay",
+                "Task-level performance translation",
+                "16,278 questions and 81,390 natural pools; DS-DS",
+                "formal candidate correctness labels",
+                "Fig. 3",
+                "derived_summaries/natural_replay_accuracy_summary.csv",
+            ],
+            [
+                "False-majority diffusion",
+                "Bounded mechanism control",
+                "713 accepted minority-correct pools",
+                "formal candidate correctness labels",
+                "Fig. 4",
+                "derived_summaries/minority_diffusion_mechanism_summary.csv",
+            ],
+            [
+                "Prompt-information perturbation",
+                "Information-channel control",
+                "713 matched reranked pools under prompt modes",
+                "formal candidate correctness labels",
+                "Fig. 4",
+                "derived_summaries/perturbation_prompt_mode_summary.csv",
+            ],
+            [
+                "Pool-size and cost frontier",
+                "Budget and scaling implication",
+                "strict-common natural pool-size 2x2",
+                "formal candidate correctness labels",
+                "Fig. 4",
+                "derived_summaries/pool_size_cost_summary.csv",
+            ],
+            [
+                "Question-matched Mimo pool-setting contrast",
+                "Generator-conditioned opportunity sensitivity",
+                "Same 11,241 benchmark-question pairs at k=16; generated traces remain setting-specific",
+                "formal candidate correctness labels",
+                "Extended Data Fig. 6 and Methods",
+                "derived_summaries/pool_setting_k16_question_matched_strategy_summary.csv",
+            ],
+        ],
+        ["Evidence", "Status", "Unit", "Label source", "Manuscript role", "Primary derived file"],
+    )
+    index += """
+
+## Naming Rules For The Manuscript
+
+1. Use **four-benchmark modelling set** for MMLU-Pro, GPQA, MedXpertQA and MuSR.
+2. Use **HLE MC external validation** for HLE multiple-choice.
+3. Use **HLE QA open-answer diagnostic** for HLE open-answer, because labels are reference-answer equivalence judgements.
+4. Use **complete natural-pool replay** for the DS-DS 16,278-question task-accuracy replay.
+5. Use **balanced** only for controlled diagnostics or stress tests, not for real task-prevalence claims.
+6. Use **seven-cell generator-judge sensitivity** only when the figure or table explicitly compares model-pair sensitivity; do not describe it as a complete 3 x 3 matrix.
+7. Distinguish **Mimo (no-think)** from **Mimo (medium-thinking)** at every first use, and state whether the generator bank or judge setting changed. Legacy `default` keys are provenance labels only.
+"""
+    (OUT_DIR.parent / "EVIDENCE_INDEX.md").write_text(index, encoding="utf-8")
+
+
+def main() -> None:
+    OUT_DIR.mkdir(parents=True, exist_ok=True)
+    (OUT_DIR / "scripts").mkdir(parents=True, exist_ok=True)
+    build_selector_boundary_summaries()
+    build_generator_bank_question_matched_summaries()
+    build_replay_summaries()
+    build_mechanism_summaries()
+    build_pool_size_cost_summary()
+    build_k16_question_matched_pool_setting_summary()
+    write_readme_and_index()
+
+
+if __name__ == "__main__":
+    main()

data/external/evidence/formal/five_benchmark_cost_efficiency/README.md

@@ -0,0 +1,18 @@
+# Global Leaderboard Pool-Size Cost-Efficiency Evidence
+
+Status: formal compact copy.
+
+This evidence package supports the claim that increasing sample budget has diminishing task-accuracy returns once selector cost is included. It is derived from the formal package at `results/formal/five_benchmark_cost_efficiency/`.
+
+Primary tables:
+
+- `natural_pool_size_strategy_accuracy_cost.csv`
+- `natural_pool_size_incremental_cost_effectiveness.csv`
+- `natural_pool_size_cost_frontier_source_data.csv`
+- `balanced_pool_size_auc.csv`
+
+Caveats:
+
+- Natural rows are strict-common and parse-ok-filtered.
+- Balanced rows are robustness/stress-test evidence.
+- Paid-equivalent costs are estimates from `price_model.csv`.

data/external/evidence/formal/five_benchmark_cost_efficiency/balanced_pool_size_auc.csv

@@ -0,0 +1,139 @@
+experiment_id,population,pool_size,correct_count,wrong_count,correct_ratio,benchmark,generator,selector,cell_id,n_pools,mean_auc,ci_low,ci_high,top1_correct_rate
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,__global__,deepseek,deepseek,deepseek_to_deepseek,2104,0.662864,0.647014,0.679757,0.536597
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,gpqa,deepseek,deepseek,deepseek_to_deepseek,194,0.695876,0.641710,0.751031,0.577320
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,hle_text_mc,deepseek,deepseek,deepseek_to_deepseek,435,0.497318,0.459655,0.536801,0.328736
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,medxpertqa,deepseek,deepseek,deepseek_to_deepseek,489,0.668030,0.630760,0.701534,0.503067
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,mmlu_pro,deepseek,deepseek,deepseek_to_deepseek,492,0.852981,0.828235,0.876694,0.756098
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,musr,deepseek,deepseek,deepseek_to_deepseek,494,0.601215,0.562011,0.639659,0.518219
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,__global__,deepseek,mimo,deepseek_to_mimo,2135,0.599063,0.584067,0.619290,0.428103
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,gpqa,deepseek,mimo,deepseek_to_mimo,197,0.570220,0.510745,0.617682,0.375635
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,hle_text_mc,deepseek,mimo,deepseek_to_mimo,439,0.453303,0.419894,0.492426,0.273349
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,medxpertqa,deepseek,mimo,deepseek_to_mimo,500,0.598667,0.566983,0.625433,0.350000
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,mmlu_pro,deepseek,mimo,deepseek_to_mimo,499,0.808951,0.785888,0.839078,0.669339
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,musr,deepseek,mimo,deepseek_to_mimo,500,0.529333,0.493200,0.570350,0.422000
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,__global__,mimo,deepseek,mimo_to_deepseek,2132,0.699656,0.685331,0.715060,0.545966
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,gpqa,mimo,deepseek,mimo_to_deepseek,223,0.751868,0.699552,0.794581,0.632287
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,hle_text_mc,mimo,deepseek,mimo_to_deepseek,425,0.480784,0.451275,0.517647,0.270588
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,medxpertqa,mimo,deepseek,mimo_to_deepseek,494,0.740891,0.714727,0.771964,0.550607
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,mmlu_pro,mimo,deepseek,mimo_to_deepseek,496,0.871640,0.850101,0.894691,0.774194
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,musr,mimo,deepseek,mimo_to_deepseek,494,0.650472,0.611336,0.689103,0.510121
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,__global__,mimo,mimo,mimo_to_mimo,2137,0.659803,0.645757,0.674957,0.465138
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,gpqa,mimo,mimo,mimo_to_mimo,233,0.666667,0.615629,0.711767,0.484979
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,hle_text_mc,mimo,mimo,mimo_to_mimo,444,0.504505,0.469895,0.537932,0.252252
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,medxpertqa,mimo,mimo,mimo_to_mimo,482,0.649378,0.621680,0.691598,0.421162
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,mmlu_pro,mimo,mimo,mimo_to_mimo,487,0.854209,0.832272,0.874059,0.718686
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,1,3,0.250000,musr,mimo,mimo,mimo_to_mimo,491,0.614392,0.585132,0.656840,0.439919
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,__global__,deepseek,deepseek,deepseek_to_deepseek,2124,0.767302,0.751271,0.782548,0.718456
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,gpqa,deepseek,deepseek,deepseek_to_deepseek,207,0.852657,0.810145,0.887681,0.811594
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,hle_text_mc,deepseek,deepseek,deepseek_to_deepseek,435,0.613793,0.569454,0.651236,0.544828
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,medxpertqa,deepseek,deepseek,deepseek_to_deepseek,492,0.768801,0.738135,0.790409,0.701220
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,mmlu_pro,deepseek,deepseek,deepseek_to_deepseek,494,0.892713,0.870154,0.915245,0.858300
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,musr,deepseek,deepseek,deepseek_to_deepseek,496,0.739919,0.705885,0.775202,0.709677
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,__global__,deepseek,mimo,deepseek_to_mimo,2126,0.693203,0.675738,0.710345,0.631232
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,gpqa,deepseek,mimo,deepseek_to_mimo,209,0.657895,0.604635,0.709390,0.598086
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,hle_text_mc,deepseek,mimo,deepseek_to_mimo,437,0.572082,0.535169,0.609568,0.491991
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,medxpertqa,deepseek,mimo,deepseek_to_mimo,498,0.707329,0.674937,0.732957,0.624498
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,mmlu_pro,deepseek,mimo,deepseek_to_mimo,496,0.830141,0.803427,0.851071,0.774194
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,musr,deepseek,mimo,deepseek_to_mimo,486,0.663066,0.637834,0.700939,0.631687
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,__global__,mimo,deepseek,mimo_to_deepseek,2162,0.787812,0.774509,0.799497,0.751619
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,gpqa,mimo,deepseek,mimo_to_deepseek,225,0.787778,0.749944,0.830111,0.800000
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,2,2,0.500000,hle_text_mc,mimo,deepseek,mimo_to_deepseek,437,0.622998,0.584039,0.656836,0.535469
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data/external/evidence/formal/five_benchmark_cost_efficiency/balanced_pool_size_incremental_cost_effectiveness.csv

@@ -0,0 +1,289 @@
+experiment_id,population,pool_size,benchmark,generator,selector,cell_id,cost_scenario,strategy_a,strategy_b,delta_accuracy,delta_correct_questions,delta_cost_usd_normalized,incremental_cost_per_extra_correct
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+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,rank@12,majority@12,-0.054092,-39.000000,0.015940,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,oracle@12,majority@12,0.177531,128.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,rank@12,single@1,0.163661,118.000000,0.403001,0.003415
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,majority@12,single@1,0.217753,157.000000,1.386186,0.008829
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,rank@12,majority@12,-0.054092,-39.000000,0.312321,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,oracle@12,majority@12,0.177531,128.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,rank@12,single@1,0.163661,118.000000,1.698507,0.014394
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,majority@12,single@1,0.213277,151.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,rank@12,majority@12,-0.028249,-20.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,oracle@12,majority@12,0.180791,128.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,rank@12,single@1,0.185028,131.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,majority@12,single@1,0.213277,151.000000,0.381494,0.002526
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,rank@12,majority@12,-0.028249,-20.000000,0.015442,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,oracle@12,majority@12,0.180791,128.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,rank@12,single@1,0.185028,131.000000,0.396936,0.003030
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,majority@12,single@1,0.213277,151.000000,1.365608,0.009044
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,rank@12,majority@12,-0.028249,-20.000000,0.303136,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,oracle@12,majority@12,0.180791,128.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,rank@12,single@1,0.185028,131.000000,1.668744,0.012739
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@12,single@1,0.207801,309.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@12,majority@12,-0.083389,-124.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@12,single@1,0.124412,185.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@12,single@1,0.207801,309.000000,0.479296,0.001551
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@12,majority@12,-0.083389,-124.000000,0.027909,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@12,single@1,0.124412,185.000000,0.507205,0.002742
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_miss,majority@12,single@1,0.207801,309.000000,1.733355,0.005610
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_miss,rank@12,majority@12,-0.083389,-124.000000,0.395763,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_miss,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_miss,rank@12,single@1,0.124412,185.000000,2.129118,0.011509
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,observed_free,majority@12,single@1,0.207739,306.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,observed_free,rank@12,majority@12,-0.183299,-270.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,observed_free,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,observed_free,rank@12,single@1,0.024440,36.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_hit,majority@12,single@1,0.207739,306.000000,0.474442,0.001550
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_hit,rank@12,majority@12,-0.183299,-270.000000,0.027233,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_hit,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_hit,rank@12,single@1,0.024440,36.000000,0.501675,0.013935
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_miss,majority@12,single@1,0.207739,306.000000,1.716261,0.005609
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_miss,rank@12,majority@12,-0.183299,-270.000000,0.386018,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_miss,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,deepseek,mimo,deepseek_to_mimo,paid_equivalent_cache_miss,rank@12,single@1,0.024440,36.000000,2.102279,0.058397
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,observed_free,majority@12,single@1,0.130435,3.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,observed_free,rank@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,observed_free,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,observed_free,rank@12,single@1,0.130435,3.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,majority@12,single@1,0.130435,3.000000,0.009879,0.003293
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,rank@12,majority@12,0.000000,0.000000,0.000457,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_hit,rank@12,single@1,0.130435,3.000000,0.010336,0.003445
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,majority@12,single@1,0.130435,3.000000,0.027616,0.009205
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,rank@12,majority@12,0.000000,0.000000,0.007395,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,deepseek,mimo_to_deepseek,paid_equivalent_cache_miss,oracle@12,majority@12,0.000000,0.000000,0.000000,
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+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,majority@12,single@1,0.130435,3.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,rank@12,majority@12,-0.130435,-3.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,observed_free,rank@12,single@1,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,majority@12,single@1,0.130435,3.000000,0.009879,0.003293
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,rank@12,majority@12,-0.130435,-3.000000,0.000450,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_hit,rank@12,single@1,0.000000,0.000000,0.010329,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,majority@12,single@1,0.130435,3.000000,0.027616,0.009205
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,rank@12,majority@12,-0.130435,-3.000000,0.007285,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,oracle@12,majority@12,0.000000,0.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,__global__,mimo,mimo,mimo_to_mimo,paid_equivalent_cache_miss,rank@12,single@1,0.000000,0.000000,0.034901,

data/external/evidence/formal/five_benchmark_cost_efficiency/balanced_pool_size_strategy_accuracy_cost.csv

@@ -0,0 +1,289 @@
+experiment_id,population,pool_size,rank_source,benchmark,generator,selector,cell_id,strategy,cost_scenario,currency,n_questions,accuracy,ci_low,ci_high,correct_questions,generation_requests,selector_requests,prompt_tokens,generation_prompt_tokens,selector_prompt_tokens,generation_completion_tokens,selector_completion_tokens,completion_tokens,total_tokens,estimated_cost_native,estimated_cost_usd_normalized,relative_cost_vs_single,cost_per_correct,accuracy_status
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,observed_free,USD,2104,0.536597,0.515209,0.557985,1129.000000,8416,2104,8014669,5701728,2312941,911993,39976,951969,8966638,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_miss,USD,2104,0.536597,0.515209,0.557985,1129.000000,8416,2104,8014669,5701728,2312941,911993,39976,951969,8966638,1.388605,1.388605,5.288433,0.001230,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_hit,USD,2104,0.536597,0.515209,0.557985,1129.000000,8416,2104,8014669,5701728,2312941,911993,39976,951969,8966638,0.288992,0.288992,4.311254,0.000256,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,observed_free,USD,2104,0.095532,0.083175,0.108365,201.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_miss,USD,2104,0.095532,0.083175,0.108365,201.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,1.053600,1.053600,4.012583,0.005242,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_hit,USD,2104,0.095532,0.083175,0.108365,201.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,0.271323,0.271323,4.047664,0.001350,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,observed_free,USD,2104,1.000000,1.000000,1.000000,2104.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_miss,USD,2104,1.000000,1.000000,1.000000,2104.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,1.053600,1.053600,4.012583,0.000501,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_hit,USD,2104,1.000000,1.000000,1.000000,2104.000000,8416,0,5701728,5701728,0,911993,0,911993,6613721,0.271323,0.271323,4.047664,0.000129,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,2104,0.242871,0.224810,0.261407,511.000000,2104,0,1425236,1425236,0,225146,0,225146,1650382,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,2104,0.242871,0.224810,0.261407,511.000000,2104,0,1425236,1425236,0,225146,0,225146,1650382,0.262574,0.262574,1.000000,0.000514,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,2104,0.242871,0.224810,0.261407,511.000000,2104,0,1425236,1425236,0,225146,0,225146,1650382,0.067032,0.067032,1.000000,0.000131,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,observed_free,USD,2135,0.428103,0.407026,0.449180,914.000000,8540,2135,8135056,5787898,2347158,925028,40565,965593,9100649,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_miss,MIXED,2135,0.428103,0.407026,0.449180,914.000000,8540,2135,8135056,5787898,2347158,925028,40565,965593,9100649,3.497602,1.404250,5.270358,0.001536,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_hit,MIXED,2135,0.428103,0.407026,0.449180,914.000000,8540,2135,8135056,5787898,2347158,925028,40565,965593,9100649,0.403287,0.292879,4.310531,0.000320,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,observed_free,USD,2135,0.095550,0.083372,0.108197,204.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_miss,MIXED,2135,0.095550,0.083372,0.108197,204.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,1.069314,1.069314,4.013294,0.005242,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_hit,MIXED,2135,0.095550,0.083372,0.108197,204.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,0.275214,0.275214,4.050541,0.001349,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,observed_free,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_miss,MIXED,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,1.069314,1.069314,4.013294,0.000501,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_hit,MIXED,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5787898,5787898,0,925028,0,925028,6712926,0.275214,0.275214,4.050541,0.000129,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,2135,0.243091,0.224824,0.261358,519.000000,2135,0,1446777,1446777,0,228194,0,228194,1674971,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,2135,0.243091,0.224824,0.261358,519.000000,2135,0,1446777,1446777,0,228194,0,228194,1674971,0.266443,0.266443,1.000000,0.000513,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,2135,0.243091,0.224824,0.261358,519.000000,2135,0,1446777,1446777,0,228194,0,228194,1674971,0.067945,0.067945,1.000000,0.000131,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,observed_free,USD,2132,0.545966,0.524859,0.567073,1164.000000,8528,2132,8699068,5710638,2988430,1585485,40508,1625993,10325061,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_miss,MIXED,2132,0.545966,0.524859,0.567073,1164.000000,8528,2132,8699068,5710638,2988430,1585485,40508,1625993,10325061,9.311330,1.654772,5.402279,0.001422,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_hit,MIXED,2132,0.545966,0.524859,0.567073,1164.000000,8528,2132,8699068,5710638,2988430,1585485,40508,1625993,10325061,3.304893,0.472839,4.171311,0.000406,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,observed_free,USD,2132,0.136023,0.121482,0.150563,290.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_miss,MIXED,2132,0.136023,0.121482,0.150563,290.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,8.881608,1.225049,3.999376,0.004224,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_hit,MIXED,2132,0.136023,0.121482,0.150563,290.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,3.285183,0.453129,3.997433,0.001563,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,observed_free,USD,2132,1.000000,1.000000,1.000000,2132.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_miss,MIXED,2132,1.000000,1.000000,1.000000,2132.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,8.881608,1.225049,3.999376,0.000575,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_hit,MIXED,2132,1.000000,1.000000,1.000000,2132.000000,8528,0,5710638,5710638,0,1585485,0,1585485,7296123,3.285183,0.453129,3.997433,0.000213,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,2132,0.231707,0.213884,0.249531,494.000000,2132,0,1427472,1427472,0,396636,0,396636,1824108,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,2132,0.231707,0.213884,0.249531,494.000000,2132,0,1427472,1427472,0,396636,0,396636,1824108,2.220744,0.306310,1.000000,0.000620,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,2132,0.231707,0.213884,0.249531,494.000000,2132,0,1427472,1427472,0,396636,0,396636,1824108,0.821821,0.113355,1.000000,0.000229,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,observed_free,USD,2137,0.465138,0.444080,0.486196,994.000000,8548,2137,8687418,5692676,2994742,1596348,40603,1636951,10324369,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_miss,CNY,2137,0.465138,0.444080,0.486196,994.000000,8548,2137,8687418,5692676,2994742,1596348,40603,1636951,10324369,11.961320,1.649837,5.387786,0.001660,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_hit,CNY,2137,0.465138,0.444080,0.486196,994.000000,8548,2137,8687418,5692676,2994742,1596348,40603,1636951,10324369,3.447650,0.475538,4.176148,0.000478,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,observed_free,USD,2137,0.134300,0.119794,0.148807,287.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_miss,CNY,2137,0.134300,0.119794,0.148807,287.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,8.885372,1.225569,4.002276,0.004270,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_hit,CNY,2137,0.134300,0.119794,0.148807,287.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,3.306550,0.456076,4.005234,0.001589,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,observed_free,USD,2137,1.000000,1.000000,1.000000,2137.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_miss,CNY,2137,1.000000,1.000000,1.000000,2137.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,8.885372,1.225569,4.002276,0.000573,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_hit,CNY,2137,1.000000,1.000000,1.000000,2137.000000,8548,0,5692676,5692676,0,1596348,0,1596348,7289024,3.306550,0.456076,4.005234,0.000213,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,2137,0.235845,0.218063,0.254095,504.000000,2137,0,1422981,1422981,0,398548,0,398548,1821529,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,2137,0.235845,0.218063,0.254095,504.000000,2137,0,1422981,1422981,0,398548,0,398548,1821529,2.220077,0.306218,1.000000,0.000608,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_1c3w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,2137,0.235845,0.218063,0.254095,504.000000,2137,0,1422981,1422981,0,398548,0,398548,1821529,0.825556,0.113870,1.000000,0.000226,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,observed_free,USD,2124,0.718456,0.699153,0.737288,1526.000000,8496,2124,8080469,5763426,2317043,900885,40356,941241,9021710,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_miss,USD,2124,0.718456,0.699153,0.737288,1526.000000,8496,2124,8080469,5763426,2317043,900885,40356,941241,9021710,1.394813,1.394813,5.273594,0.000914,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_hit,USD,2124,0.718456,0.699153,0.737288,1526.000000,8496,2124,8080469,5763426,2317043,900885,40356,941241,9021710,0.286173,0.286173,4.282040,0.000188,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,observed_free,USD,2124,0.841808,0.826271,0.857345,1788.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_miss,USD,2124,0.841808,0.826271,0.857345,1788.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,1.059127,1.059127,4.004412,0.000592,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_hit,USD,2124,0.841808,0.826271,0.857345,1788.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,0.268385,0.268385,4.015876,0.000150,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,observed_free,USD,2124,1.000000,1.000000,1.000000,2124.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_miss,USD,2124,1.000000,1.000000,1.000000,2124.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,1.059127,1.059127,4.004412,0.000499,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_hit,USD,2124,1.000000,1.000000,1.000000,2124.000000,8496,0,5763426,5763426,0,900885,0,900885,6664311,0.268385,0.268385,4.015876,0.000126,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,2124,0.500471,0.479284,0.521657,1063.000000,2124,0,1440666,1440666,0,224275,0,224275,1664941,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,2124,0.500471,0.479284,0.521657,1063.000000,2124,0,1440666,1440666,0,224275,0,224275,1664941,0.264490,0.264490,1.000000,0.000249,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,2124,0.500471,0.479284,0.521657,1063.000000,2124,0,1440666,1440666,0,224275,0,224275,1664941,0.066831,0.066831,1.000000,0.000063,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,observed_free,USD,2126,0.631232,0.610536,0.651458,1342.000000,8504,2126,8023210,5716327,2306883,902523,40394,942917,8966127,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_miss,MIXED,2126,0.631232,0.610536,0.651458,1342.000000,8504,2126,8023210,5716327,2306883,902523,40394,942917,8966127,3.440663,1.382326,5.256532,0.001030,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_hit,MIXED,2126,0.631232,0.610536,0.651458,1342.000000,8504,2126,8023210,5716327,2306883,902523,40394,942917,8966127,0.395638,0.286219,4.276457,0.000213,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,observed_free,USD,2126,0.842427,0.826905,0.857949,1791.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_miss,MIXED,2126,0.842427,0.826905,0.857949,1791.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,1.052992,1.052992,4.004183,0.000588,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_hit,MIXED,2126,0.842427,0.826905,0.857949,1791.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,0.268712,0.268712,4.014881,0.000150,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,observed_free,USD,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_miss,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,1.052992,1.052992,4.004183,0.000495,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_hit,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5716327,5716327,0,902523,0,902523,6618850,0.268712,0.268712,4.014881,0.000126,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,2126,0.499530,0.478363,0.520696,1062.000000,2126,0,1428888,1428888,0,224744,0,224744,1653632,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,2126,0.499530,0.478363,0.520696,1062.000000,2126,0,1428888,1428888,0,224744,0,224744,1653632,0.262973,0.262973,1.000000,0.000248,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,2126,0.499530,0.478363,0.520696,1062.000000,2126,0,1428888,1428888,0,224744,0,224744,1653632,0.066929,0.066929,1.000000,0.000063,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,observed_free,USD,2162,0.751619,0.733117,0.769658,1625.000000,8648,2162,8874761,5878368,2996393,1551861,41078,1592939,10467700,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_miss,MIXED,2162,0.751619,0.733117,0.769658,1625.000000,8648,2162,8874761,5878368,2996393,1551861,41078,1592939,10467700,9.413087,1.669906,5.401552,0.001028,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_hit,MIXED,2162,0.751619,0.733117,0.769658,1625.000000,8648,2162,8874761,5878368,2996393,1551861,41078,1592939,10467700,3.241181,0.464208,4.199723,0.000286,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,observed_free,USD,2162,0.896855,0.883904,0.909343,1939.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_miss,MIXED,2162,0.896855,0.883904,0.909343,1939.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,8.982090,1.238909,4.007430,0.000639,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_hit,MIXED,2162,0.896855,0.883904,0.909343,1939.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,3.221289,0.444316,4.019759,0.000229,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,observed_free,USD,2162,1.000000,1.000000,1.000000,2162.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_miss,MIXED,2162,1.000000,1.000000,1.000000,2162.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,8.982090,1.238909,4.007430,0.000573,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_hit,MIXED,2162,1.000000,1.000000,1.000000,2162.000000,8648,0,5878368,5878368,0,1551861,0,1551861,7430229,3.221289,0.444316,4.019759,0.000206,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,2162,0.568918,0.548104,0.589732,1230.000000,2162,0,1469382,1469382,0,385989,0,385989,1855371,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,2162,0.568918,0.548104,0.589732,1230.000000,2162,0,1469382,1469382,0,385989,0,385989,1855371,2.241360,0.309153,1.000000,0.000251,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,2162,0.568918,0.548104,0.589732,1230.000000,2162,0,1469382,1469382,0,385989,0,385989,1855371,0.801366,0.110533,1.000000,0.000090,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,observed_free,USD,2174,0.685373,0.665593,0.704692,1490.000000,8696,2174,8916328,5903628,3012700,1561991,41306,1603297,10519625,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_miss,CNY,2174,0.685373,0.665593,0.704692,1490.000000,8696,2174,8916328,5903628,3012700,1561991,41306,1603297,10519625,12.122922,1.672127,5.380212,0.001122,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_hit,CNY,2174,0.685373,0.665593,0.704692,1490.000000,8696,2174,8916328,5903628,3012700,1561991,41306,1603297,10519625,3.384921,0.466886,4.194164,0.000313,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,observed_free,USD,2174,0.896964,0.884085,0.909384,1950.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_miss,CNY,2174,0.896964,0.884085,0.909384,1950.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,9.027610,1.245188,4.006500,0.000639,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_hit,CNY,2174,0.896964,0.884085,0.909384,1950.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,3.242055,0.447180,4.017140,0.000229,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,observed_free,USD,2174,1.000000,1.000000,1.000000,2174.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_miss,CNY,2174,1.000000,1.000000,1.000000,2174.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,9.027610,1.245188,4.006500,0.000573,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_hit,CNY,2174,1.000000,1.000000,1.000000,2174.000000,8696,0,5903628,5903628,0,1561991,0,1561991,7465619,3.242055,0.447180,4.017140,0.000206,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,2174,0.567617,0.546918,0.588316,1234.000000,2174,0,1475696,1475696,0,388772,0,388772,1864468,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,2174,0.567617,0.546918,0.588316,1234.000000,2174,0,1475696,1475696,0,388772,0,388772,1864468,2.253240,0.310792,1.000000,0.000252,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_2c2w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,2174,0.567617,0.546918,0.588316,1234.000000,2174,0,1475696,1475696,0,388772,0,388772,1864468,0.807058,0.111318,1.000000,0.000090,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,observed_free,USD,2135,0.859953,0.844965,0.874473,1836.000000,8540,2135,8091361,5781608,2309753,889226,40565,929791,9021152,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_miss,USD,2135,0.859953,0.844965,0.874473,1836.000000,8540,2135,8091361,5781608,2309753,889226,40565,929791,9021152,1.393132,1.393132,5.262444,0.000759,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_hit,USD,2135,0.859953,0.844965,0.874473,1836.000000,8540,2135,8091361,5781608,2309753,889226,40565,929791,9021152,0.282997,0.282997,4.258732,0.000154,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,observed_free,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_miss,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,1.058408,1.058408,3.998051,0.000496,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_hit,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,0.265172,0.265172,3.990489,0.000124,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,observed_free,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_miss,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,1.058408,1.058408,3.998051,0.000496,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_hit,USD,2135,1.000000,1.000000,1.000000,2135.000000,8540,0,5781608,5781608,0,889226,0,889226,6670834,0.265172,0.265172,3.990489,0.000124,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,2135,0.765340,0.747073,0.783138,1634.000000,2135,0,1445189,1445189,0,222873,0,222873,1668062,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,2135,0.765340,0.747073,0.783138,1634.000000,2135,0,1445189,1445189,0,222873,0,222873,1668062,0.264731,0.264731,1.000000,0.000162,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,2135,0.765340,0.747073,0.783138,1634.000000,2135,0,1445189,1445189,0,222873,0,222873,1668062,0.066451,0.066451,1.000000,0.000041,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,observed_free,USD,2126,0.784572,0.767168,0.801976,1668.000000,8504,2126,8037979,5741761,2296218,885547,40394,925941,8963920,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_miss,MIXED,2126,0.784572,0.767168,0.801976,1668.000000,8504,2126,8037979,5741761,2296218,885547,40394,925941,8963920,3.428806,1.379663,5.244312,0.000827,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_hit,MIXED,2126,0.784572,0.767168,0.801976,1668.000000,8504,2126,8037979,5741761,2296218,885547,40394,925941,8963920,0.390742,0.281508,4.254636,0.000169,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,observed_free,USD,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_miss,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,1.051800,1.051800,3.998054,0.000495,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_hit,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,0.264030,0.264030,3.990478,0.000124,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,observed_free,USD,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_miss,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,1.051800,1.051800,3.998054,0.000495,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_hit,MIXED,2126,1.000000,1.000000,1.000000,2126.000000,8504,0,5741761,5741761,0,885547,0,885547,6627308,0.264030,0.264030,3.990478,0.000124,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,2126,0.764346,0.746002,0.782220,1625.000000,2126,0,1435228,1435228,0,221951,0,221951,1657179,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,2126,0.764346,0.746002,0.782220,1625.000000,2126,0,1435228,1435228,0,221951,0,221951,1657179,0.263078,0.263078,1.000000,0.000162,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,2126,0.764346,0.746002,0.782220,1625.000000,2126,0,1435228,1435228,0,221951,0,221951,1657179,0.066165,0.066165,1.000000,0.000041,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,observed_free,USD,1624,0.885468,0.869458,0.900862,1438.000000,6496,1624,6924834,4684752,2240082,1087774,30856,1118630,8043464,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_miss,MIXED,1624,0.885468,0.869458,0.900862,1438.000000,6496,1624,6924834,4684752,2240082,1087774,30856,1118630,8043464,7.182551,1.268499,5.378049,0.000882,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_hit,MIXED,1624,0.885468,0.869458,0.900862,1438.000000,6496,1624,6924834,4684752,2240082,1087774,30856,1118630,8043464,2.284155,0.327911,4.227074,0.000228,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,observed_free,USD,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_miss,MIXED,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,6.860300,0.946248,4.011803,0.000583,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_hit,MIXED,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,2.269243,0.312999,4.034844,0.000193,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,observed_free,USD,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_miss,MIXED,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,6.860300,0.946248,4.011803,0.000583,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_hit,MIXED,1624,1.000000,1.000000,1.000000,1624.000000,6496,0,4684752,4684752,0,1087774,0,1087774,5772526,2.269243,0.312999,4.034844,0.000193,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,1624,0.810961,0.791872,0.830049,1317.000000,1624,0,1171037,1171037,0,269496,0,269496,1440533,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,1624,0.810961,0.791872,0.830049,1317.000000,1624,0,1171037,1171037,0,269496,0,269496,1440533,1.710029,0.235866,1.000000,0.000179,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,1624,0.810961,0.791872,0.830049,1317.000000,1624,0,1171037,1171037,0,269496,0,269496,1440533,0.562413,0.077574,1.000000,0.000059,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,observed_free,USD,1618,0.802225,0.782447,0.821384,1298.000000,6472,1618,6900855,4667680,2233175,1085065,30742,1115807,8016662,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_miss,CNY,1618,0.802225,0.782447,0.821384,1298.000000,6472,1618,6900855,4667680,2233175,1085065,30742,1115807,8016662,9.132469,1.259651,5.357778,0.000970,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_hit,CNY,1618,0.802225,0.782447,0.821384,1298.000000,6472,1618,6900855,4667680,2233175,1085065,30742,1115807,8016662,2.369631,0.326846,4.223253,0.000252,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,observed_free,USD,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_miss,CNY,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,6.837810,0.943146,4.011561,0.000583,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_hit,CNY,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,2.263484,0.312205,4.034073,0.000193,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,observed_free,USD,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_miss,CNY,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,6.837810,0.943146,4.011561,0.000583,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_hit,CNY,1618,1.000000,1.000000,1.000000,1618.000000,6472,0,4667680,4667680,0,1085065,0,1085065,5752745,2.263484,0.312205,4.034073,0.000193,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,1618,0.811496,0.792336,0.830655,1313.000000,1618,0,1166769,1166769,0,268877,0,268877,1435646,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,1618,0.811496,0.792336,0.830655,1313.000000,1618,0,1166769,1166769,0,268877,0,268877,1435646,1.704523,0.235107,1.000000,0.000179,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k4_3c1w,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,1618,0.811496,0.792336,0.830655,1313.000000,1618,0,1166769,1166769,0,268877,0,268877,1435646,0.561089,0.077392,1.000000,0.000059,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,observed_free,USD,1769,0.497456,0.474279,0.520633,880.000000,21228,1769,15920316,12533974,3386342,2242583,86681,2329264,18249580,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_miss,USD,1769,0.497456,0.474279,0.520633,880.000000,21228,1769,15920316,12533974,3386342,2242583,86681,2329264,18249580,2.881038,2.881038,14.507541,0.003274,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_hit,USD,1769,0.497456,0.474279,0.520633,880.000000,21228,1769,15920316,12533974,3386342,2242583,86681,2329264,18249580,0.696771,0.696771,12.596193,0.000792,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,observed_free,USD,1769,0.425099,0.401922,0.448276,752.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_miss,USD,1769,0.425099,0.401922,0.448276,752.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,2.382680,2.382680,11.998046,0.003168,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_hit,USD,1769,0.425099,0.401922,0.448276,752.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,0.663018,0.663018,11.986008,0.000882,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,observed_free,USD,1769,1.000000,1.000000,1.000000,1769.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_miss,USD,1769,1.000000,1.000000,1.000000,1769.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,2.382680,2.382680,11.998046,0.001347,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_hit,USD,1769,1.000000,1.000000,1.000000,1769.000000,21228,0,12533974,12533974,0,2242583,0,2242583,14776557,0.663018,0.663018,11.986008,0.000375,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,1769,0.248728,0.228943,0.269079,440.000000,1769,0,1044265,1044265,0,187115,0,187115,1231380,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,1769,0.248728,0.228943,0.269079,440.000000,1769,0,1044265,1044265,0,187115,0,187115,1231380,0.198589,0.198589,1.000000,0.000451,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,1769,0.248728,0.228943,0.269079,440.000000,1769,0,1044265,1044265,0,187115,0,187115,1231380,0.055316,0.055316,1.000000,0.000126,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,observed_free,USD,1708,0.411593,0.388173,0.435012,703.000000,20496,1708,15417697,12149435,3268262,2159958,83692,2243650,17661347,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_miss,MIXED,1708,0.411593,0.388173,0.435012,703.000000,20496,1708,15417697,12149435,3268262,2159958,83692,2243650,17661347,5.741355,2.779591,14.469726,0.003954,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_hit,MIXED,1708,0.411593,0.388173,0.435012,703.000000,20496,1708,15417697,12149435,3268262,2159958,83692,2243650,17661347,0.871556,0.670910,12.606825,0.000954,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,observed_free,USD,1708,0.429742,0.406323,0.453162,734.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_miss,MIXED,1708,0.429742,0.406323,0.453162,734.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,2.305709,2.305709,12.002837,0.003141,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_hit,MIXED,1708,0.429742,0.406323,0.453162,734.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,0.638807,0.638807,12.003589,0.000870,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,observed_free,USD,1708,1.000000,1.000000,1.000000,1708.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_miss,MIXED,1708,1.000000,1.000000,1.000000,1708.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,2.305709,2.305709,12.002837,0.001350,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_hit,MIXED,1708,1.000000,1.000000,1.000000,1708.000000,20496,0,12149435,12149435,0,2159958,0,2159958,14309393,0.638807,0.638807,12.003589,0.000374,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,1708,0.248244,0.227752,0.268735,424.000000,1708,0,1012232,1012232,0,179943,0,179943,1192175,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,1708,0.248244,0.227752,0.268735,424.000000,1708,0,1012232,1012232,0,179943,0,179943,1192175,0.192097,0.192097,1.000000,0.000453,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,1708,0.248244,0.227752,0.268735,424.000000,1708,0,1012232,1012232,0,179943,0,179943,1192175,0.053218,0.053218,1.000000,0.000126,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,observed_free,USD,1601,0.582136,0.557776,0.606496,932.000000,19212,1601,17833595,13160123,4673472,3486889,78449,3565338,21398933,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_miss,MIXED,1601,0.582136,0.557776,0.606496,932.000000,19212,1601,17833595,13160123,4673472,3486889,78449,3565338,21398933,20.810153,3.453342,15.097105,0.003705,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_hit,MIXED,1601,0.582136,0.557776,0.606496,932.000000,19212,1601,17833595,13160123,4673472,3486889,78449,3565338,21398933,7.272032,1.033256,12.831812,0.001109,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,observed_free,USD,1601,0.339788,0.316677,0.362898,544.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_miss,MIXED,1601,0.339788,0.316677,0.362898,544.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,20.133901,2.777090,12.140709,0.005105,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_hit,MIXED,1601,0.339788,0.316677,0.362898,544.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,7.236980,0.998204,12.396508,0.001835,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,observed_free,USD,1601,1.000000,1.000000,1.000000,1601.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_miss,MIXED,1601,1.000000,1.000000,1.000000,1601.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,20.133901,2.777090,12.140709,0.001735,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_hit,MIXED,1601,1.000000,1.000000,1.000000,1601.000000,19212,0,13160123,13160123,0,3486889,0,3486889,16647012,7.236980,0.998204,12.396508,0.000623,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,1601,0.264834,0.243598,0.286696,424.000000,1601,0,1096514,1096514,0,280932,0,280932,1377446,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,1601,0.264834,0.243598,0.286696,424.000000,1601,0,1096514,1096514,0,280932,0,280932,1377446,1.658378,0.228742,1.000000,0.000539,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,1601,0.264834,0.243598,0.286696,424.000000,1601,0,1096514,1096514,0,280932,0,280932,1377446,0.583794,0.080523,1.000000,0.000190,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,observed_free,USD,1595,0.527273,0.502821,0.551724,841.000000,19140,1595,17795677,13132643,4663034,3479086,78155,3557241,21352918,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_miss,CNY,1595,0.527273,0.502821,0.551724,841.000000,19140,1595,17795677,13132643,4663034,3479086,78155,3557241,21352918,24.910159,3.435884,15.048150,0.004085,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_hit,CNY,1595,0.527273,0.502821,0.551724,841.000000,19140,1595,17795677,13132643,4663034,3479086,78155,3557241,21352918,7.470396,1.030399,12.813199,0.001225,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,observed_free,USD,1595,0.337931,0.314734,0.361129,539.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_miss,CNY,1595,0.337931,0.314734,0.361129,539.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,20.090815,2.771147,12.136800,0.005141,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_hit,CNY,1595,0.337931,0.314734,0.361129,539.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,7.220825,0.995976,12.385142,0.001848,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,observed_free,USD,1595,1.000000,1.000000,1.000000,1595.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_miss,CNY,1595,1.000000,1.000000,1.000000,1595.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,20.090815,2.771147,12.136800,0.001737,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_hit,CNY,1595,1.000000,1.000000,1.000000,1595.000000,19140,0,13132643,13132643,0,3479086,0,3479086,16611729,7.220825,0.995976,12.385142,0.000624,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,1595,0.264577,0.243260,0.286520,422.000000,1595,0,1094226,1094226,0,280568,0,280568,1374794,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,1595,0.264577,0.243260,0.286520,422.000000,1595,0,1094226,1094226,0,280568,0,280568,1374794,1.655362,0.228326,1.000000,0.000541,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_3c9w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,1595,0.264577,0.243260,0.286520,422.000000,1595,0,1094226,1094226,0,280568,0,280568,1374794,0.583021,0.080417,1.000000,0.000191,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,observed_free,USD,1895,0.723483,0.703430,0.743536,1371.000000,22740,1895,19970269,16127652,3842617,2392326,92855,2485181,22455450,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_miss,USD,1895,0.723483,0.703430,0.743536,1371.000000,22740,1895,19970269,16127652,3842617,2392326,92855,2485181,22455450,3.491688,3.491688,14.326755,0.002547,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_hit,USD,1895,0.723483,0.703430,0.743536,1371.000000,22740,1895,19970269,16127652,3842617,2392326,92855,2485181,22455450,0.751767,0.751767,12.664325,0.000548,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,observed_free,USD,1895,0.928760,0.917150,0.940369,1760.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_miss,USD,1895,0.928760,0.917150,0.940369,1760.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,2.927723,2.927723,12.012748,0.001663,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_hit,USD,1895,0.928760,0.917150,0.940369,1760.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,0.715009,0.715009,12.045097,0.000406,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,observed_free,USD,1895,1.000000,1.000000,1.000000,1895.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_miss,USD,1895,1.000000,1.000000,1.000000,1895.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,2.927723,2.927723,12.012748,0.001545,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_hit,USD,1895,1.000000,1.000000,1.000000,1895.000000,22740,0,16127652,16127652,0,2392326,0,2392326,18519978,0.715009,0.715009,12.045097,0.000377,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,1895,0.558311,0.536148,0.580475,1058.000000,1895,0,1343708,1343708,0,198567,0,198567,1542275,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,1895,0.558311,0.536148,0.580475,1058.000000,1895,0,1343708,1343708,0,198567,0,198567,1542275,0.243718,0.243718,1.000000,0.000230,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,1895,0.558311,0.536148,0.580475,1058.000000,1895,0,1343708,1343708,0,198567,0,198567,1542275,0.059361,0.059361,1.000000,0.000056,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,observed_free,USD,1880,0.653723,0.631915,0.675000,1229.000000,22560,1880,19822805,16009387,3813418,2373832,92120,2465952,22288757,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_miss,MIXED,1880,0.653723,0.631915,0.675000,1229.000000,22560,1880,19822805,16009387,3813418,2373832,92120,2465952,22288757,6.903645,3.457388,14.292279,0.002813,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_hit,MIXED,1880,0.653723,0.631915,0.675000,1229.000000,22560,1880,19822805,16009387,3813418,2373832,92120,2465952,22288757,0.970008,0.745431,12.655445,0.000607,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,observed_free,USD,1880,0.927660,0.915957,0.939362,1744.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_miss,MIXED,1880,0.927660,0.915957,0.939362,1744.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,2.905987,2.905987,12.012877,0.001666,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_hit,MIXED,1880,0.927660,0.915957,0.939362,1744.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,0.709499,0.709499,12.045414,0.000407,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,observed_free,USD,1880,1.000000,1.000000,1.000000,1880.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_miss,MIXED,1880,1.000000,1.000000,1.000000,1880.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,2.905987,2.905987,12.012877,0.001546,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_hit,MIXED,1880,1.000000,1.000000,1.000000,1880.000000,22560,0,16009387,16009387,0,2373832,0,2373832,18383219,0.709499,0.709499,12.045414,0.000377,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,1880,0.557979,0.535638,0.580319,1049.000000,1880,0,1333854,1333854,0,197024,0,197024,1530878,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,1880,0.557979,0.535638,0.580319,1049.000000,1880,0,1333854,1333854,0,197024,0,197024,1530878,0.241906,0.241906,1.000000,0.000231,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,1880,0.557979,0.535638,0.580319,1049.000000,1880,0,1333854,1333854,0,197024,0,197024,1530878,0.058902,0.058902,1.000000,0.000056,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,observed_free,USD,721,0.768377,0.737864,0.798890,554.000000,8652,721,10223518,8063312,2160206,1447811,35329,1483140,11706658,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_miss,MIXED,721,0.768377,0.737864,0.798890,554.000000,8652,721,10223518,8063312,2160206,1447811,35329,1483140,11706658,11.271255,1.823898,14.545685,0.003292,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_hit,MIXED,721,0.768377,0.737864,0.798890,554.000000,8652,721,10223518,8063312,2160206,1447811,35329,1483140,11706658,3.072829,0.437580,12.654501,0.000790,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,observed_free,USD,721,0.822469,0.794730,0.850208,593.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_miss,MIXED,721,0.822469,0.794730,0.850208,593.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,10.958934,1.511577,12.054908,0.002549,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_hit,MIXED,721,0.822469,0.794730,0.850208,593.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,3.056888,0.421640,12.193528,0.000711,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,observed_free,USD,721,1.000000,1.000000,1.000000,721.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_miss,MIXED,721,1.000000,1.000000,1.000000,721.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,10.958934,1.511577,12.054908,0.002097,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_hit,MIXED,721,1.000000,1.000000,1.000000,721.000000,8652,0,8063312,8063312,0,1447811,0,1447811,9511123,3.056888,0.421640,12.193528,0.000585,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,721,0.604716,0.568655,0.640777,436.000000,721,0,671826,671826,0,118630,0,118630,790456,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,721,0.604716,0.568655,0.640777,436.000000,721,0,671826,671826,0,118630,0,118630,790456,0.909086,0.125391,1.000000,0.000288,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,721,0.604716,0.568655,0.640777,436.000000,721,0,671826,671826,0,118630,0,118630,790456,0.250697,0.034579,1.000000,0.000079,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,observed_free,USD,708,0.790960,0.761299,0.820621,560.000000,8496,708,10070509,7942160,2128349,1426774,34692,1461466,11531975,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_miss,CNY,708,0.790960,0.761299,0.820621,560.000000,8496,708,10070509,7942160,2128349,1426774,34692,1461466,11531975,12.993441,1.792199,14.517022,0.003200,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_hit,CNY,708,0.790960,0.761299,0.820621,560.000000,8496,708,10070509,7942160,2128349,1426774,34692,1461466,11531975,3.124342,0.430944,12.671842,0.000770,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,observed_free,USD,708,0.819209,0.790960,0.847458,580.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_miss,CNY,708,0.819209,0.790960,0.847458,580.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,10.795708,1.489063,12.061585,0.002567,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_hit,CNY,708,0.819209,0.790960,0.847458,580.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,3.012391,0.415502,12.217772,0.000716,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,observed_free,USD,708,1.000000,1.000000,1.000000,708.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_miss,CNY,708,1.000000,1.000000,1.000000,708.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,10.795708,1.489063,12.061585,0.002103,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_hit,CNY,708,1.000000,1.000000,1.000000,708.000000,8496,0,7942160,7942160,0,1426774,0,1426774,9368934,3.012391,0.415502,12.217772,0.000587,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,708,0.605932,0.569209,0.641243,429.000000,708,0,661732,661732,0,116660,0,116660,778392,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,708,0.605932,0.569209,0.641243,429.000000,708,0,661732,661732,0,116660,0,116660,778392,0.895052,0.123455,1.000000,0.000288,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_6c6w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,708,0.605932,0.569209,0.641243,429.000000,708,0,661732,661732,0,116660,0,116660,778392,0.246555,0.034008,1.000000,0.000079,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,observed_free,USD,1487,0.916611,0.902488,0.930061,1363.000000,17844,1487,12652245,9971094,2681151,1766847,72863,1839710,14491955,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_miss,USD,1487,0.916611,0.902488,0.930061,1363.000000,17844,1487,12652245,9971094,2681151,1766847,72863,1839710,14491955,2.286433,2.286433,14.534107,0.001678,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_hit,USD,1487,0.916611,0.902488,0.930061,1363.000000,17844,1487,12652245,9971094,2681151,1766847,72863,1839710,14491955,0.550545,0.550545,12.702930,0.000404,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,observed_free,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_miss,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,1.890670,1.890670,12.018371,0.001271,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_hit,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,0.522636,0.522636,12.058976,0.000351,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,observed_free,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_miss,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,1.890670,1.890670,12.018371,0.001271,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_hit,USD,1487,1.000000,1.000000,1.000000,1487.000000,17844,0,9971094,9971094,0,1766847,0,1766847,11737941,0.522636,0.522636,12.058976,0.000351,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,1487,0.792199,0.771352,0.812374,1178.000000,1487,0,830721,830721,0,146477,0,146477,977198,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,1487,0.792199,0.771352,0.812374,1178.000000,1487,0,830721,830721,0,146477,0,146477,977198,0.157315,0.157315,1.000000,0.000134,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_hit,USD,1487,0.792199,0.771352,0.812374,1178.000000,1487,0,830721,830721,0,146477,0,146477,977198,0.043340,0.043340,1.000000,0.000037,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,observed_free,USD,1473,0.816701,0.797013,0.836388,1203.000000,17676,1473,12528046,9873771,2654275,1748858,72177,1821035,14349081,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_miss,MIXED,1473,0.816701,0.797013,0.836388,1203.000000,17676,1473,12528046,9873771,2654275,1748858,72177,1821035,14349081,4.670637,2.258026,14.498038,0.001877,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_hit,MIXED,1473,0.816701,0.797013,0.836388,1203.000000,17676,1473,12528046,9873771,2654275,1748858,72177,1821035,14349081,0.714766,0.544560,12.698146,0.000453,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,observed_free,USD,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_miss,MIXED,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,1.872008,1.872008,12.019545,0.001271,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_hit,MIXED,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,0.517327,0.517327,12.063122,0.000351,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,observed_free,USD,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_miss,MIXED,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,1.872008,1.872008,12.019545,0.001271,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_hit,MIXED,1473,1.000000,1.000000,1.000000,1473.000000,17676,0,9873771,9873771,0,1748858,0,1748858,11622629,0.517327,0.517327,12.063122,0.000351,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,1473,0.792261,0.771215,0.812627,1167.000000,1473,0,822614,822614,0,144933,0,144933,967547,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,1473,0.792261,0.771215,0.812627,1167.000000,1473,0,822614,822614,0,144933,0,144933,967547,0.155747,0.155747,1.000000,0.000133,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_hit,MIXED,1473,0.792261,0.771215,0.812627,1167.000000,1473,0,822614,822614,0,144933,0,144933,967547,0.042885,0.042885,1.000000,0.000037,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,observed_free,USD,23,1.000000,1.000000,1.000000,23.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_miss,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.225225,0.037441,15.407819,0.001628,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_hit,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.078016,0.011155,13.620269,0.000485,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,observed_free,USD,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_miss,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.217830,0.030046,12.364609,0.001306,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_hit,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.077559,0.010698,13.062271,0.000465,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,observed_free,USD,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_miss,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.217830,0.030046,12.364609,0.001306,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_hit,MIXED,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.077559,0.010698,13.062271,0.000465,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.017620,0.002430,1.000000,0.000122,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_hit,MIXED,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.005934,0.000819,1.000000,0.000041,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,observed_free,USD,23,0.869565,0.739130,1.000000,20.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_miss,CNY,23,0.869565,0.739130,1.000000,20.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.270653,0.037331,15.362551,0.001867,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,balanced_live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_hit,CNY,23,0.869565,0.739130,1.000000,20.000000,276,23,193703,143134,50569,37348,1127,38475,232178,0.080824,0.011148,13.611722,0.000557,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,observed_free,USD,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_miss,CNY,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.217830,0.030046,12.364609,0.001306,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_hit,CNY,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.077559,0.010698,13.062271,0.000465,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,observed_free,USD,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_miss,CNY,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.217830,0.030046,12.364609,0.001306,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_hit,CNY,23,1.000000,1.000000,1.000000,23.000000,276,0,143134,143134,0,37348,0,37348,180482,0.077559,0.010698,13.062271,0.000465,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.017620,0.002430,1.000000,0.000122,estimated
+cost_efficiency_pool_size_2x2_pilot,balanced_k12_9c3w,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_hit,CNY,23,0.869565,0.739130,1.000000,20.000000,23,0,11924,11924,0,2848,0,2848,14772,0.005934,0.000819,1.000000,0.000041,estimated

data/external/evidence/formal/five_benchmark_cost_efficiency/common_intersection_coverage.csv

@@ -0,0 +1,6 @@
+experiment_id,benchmark,common_questions_with_16_parse_ok,generator_questions_with_16_parse_ok_json,deepseek_questions_with_16_parse_ok,mimo_questions_with_16_parse_ok,mimo_medium_questions_with_16_parse_ok
+cost_efficiency_pool_size_2x2_pilot,mmlu_pro,7544,"{""deepseek"": 12028, ""mimo"": 7544}",12028,7544,0
+cost_efficiency_pool_size_2x2_pilot,gpqa,233,"{""deepseek"": 546, ""mimo"": 233}",546,233,0
+cost_efficiency_pool_size_2x2_pilot,medxpertqa,2294,"{""deepseek"": 2450, ""mimo"": 2294}",2450,2294,0
+cost_efficiency_pool_size_2x2_pilot,musr,725,"{""deepseek"": 756, ""mimo"": 725}",756,725,0
+cost_efficiency_pool_size_2x2_pilot,hle_text_mc,445,"{""deepseek"": 467, ""mimo"": 466}",467,466,0

data/external/evidence/formal/five_benchmark_cost_efficiency/coverage_by_generator.csv

@@ -0,0 +1,11 @@
+experiment_id,generator,benchmark,sample_bank_questions,parse_ok_questions,questions_with_16_parse_ok,underfilled_questions,zero_parse_ok_questions,min_parse_ok,median_parse_ok,max_parse_ok
+cost_efficiency_pool_size_2x2_pilot,deepseek,mmlu_pro,12032,12032,12028,4,0,15,16.0,128
+cost_efficiency_pool_size_2x2_pilot,deepseek,gpqa,546,546,546,0,0,16,16.0,127
+cost_efficiency_pool_size_2x2_pilot,deepseek,medxpertqa,2450,2450,2450,0,0,16,64.0,128
+cost_efficiency_pool_size_2x2_pilot,deepseek,musr,756,756,756,0,0,16,16.0,128
+cost_efficiency_pool_size_2x2_pilot,deepseek,hle_text_mc,498,497,467,30,1,3,64,128
+cost_efficiency_pool_size_2x2_pilot,mimo,mmlu_pro,12032,12029,7544,4485,3,1,16,64
+cost_efficiency_pool_size_2x2_pilot,mimo,gpqa,546,546,233,313,0,2,15.0,16
+cost_efficiency_pool_size_2x2_pilot,mimo,medxpertqa,2450,2450,2294,156,0,6,16.0,16
+cost_efficiency_pool_size_2x2_pilot,mimo,musr,756,756,725,31,0,14,16.0,16
+cost_efficiency_pool_size_2x2_pilot,mimo,hle_text_mc,498,498,466,32,0,6,16.0,128

data/external/evidence/formal/five_benchmark_cost_efficiency/formal_readiness_audit.csv

@@ -0,0 +1,13 @@
+check,status,value,notes
+repair_targets_parse_ok_above_98pct,PASS,all three repair targets >98%,See audits/repair_audit_summary.md
+primary_pool_size_ranking_cells,PASS,48,Excludes copied reused rank-16 source cells
+primary_pool_size_total_parse_ok_rate,PASS,308456/309612=0.996266,After raw-log reconciliation
+all_formal_ranking_cells,PASS,52,Includes 4 copied reused rank-16 source cells
+all_formal_total_parse_ok_rate,PASS,353418/354576=0.996734,Primary pool-size cells plus reused rank-16 provenance
+bad_jsonl,PASS,0,
+duplicate_keys,PASS,tasks=0;details=0,
+denominator_mismatch,PASS,0,
+raw_success_missing_from_details,PASS,0,
+natural_scope,PASS_WITH_CAVEAT,strict-common parse-ok-filtered,Not a full benchmark-population claim
+balanced_scope,PASS_WITH_CAVEAT,stress-test only,Sparse cells remain appendix/caveat material
+rank16_reuse_source,PASS,copied,k=8 and k=16 natural rows are traceable through copied rank-16 source

data/external/evidence/formal/five_benchmark_cost_efficiency/natural_pool_size_cost_frontier_source_data.csv

@@ -0,0 +1,257 @@
+experiment_id,population,pool_size,rank_source,benchmark,generator,selector,cell_id,strategy,cost_scenario,currency,n_questions,accuracy,ci_low,ci_high,correct_questions,generation_requests,selector_requests,prompt_tokens,generation_prompt_tokens,selector_prompt_tokens,generation_completion_tokens,selector_completion_tokens,completion_tokens,total_tokens,estimated_cost_native,estimated_cost_usd_normalized,relative_cost_vs_single,cost_per_correct,accuracy_status
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@10,observed_free,USD,11240,0.646263,0.637456,0.655071,7264.000000,112400,11240,70486834,53966048,16520786,10686517,460840,11147357,81634191,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@10,paid_equivalent_cache_miss,USD,11240,0.646263,0.637456,0.655071,7264.000000,112400,11240,70486834,53966048,16520786,10686517,460840,11147357,81634191,12.989417,12.989417,12.374456,0.001788,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@10,observed_free,USD,11240,0.624822,0.615836,0.633719,7023.000000,112400,0,53966048,53966048,0,10686517,0,10686517,64652565,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@10,paid_equivalent_cache_miss,USD,11240,0.624822,0.615836,0.633719,7023.000000,112400,0,53966048,53966048,0,10686517,0,10686517,64652565,10.547471,10.547471,10.048120,0.001502,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@10,observed_free,USD,11240,0.912811,0.907562,0.917972,10260.000000,112400,0,53966048,53966048,0,10686517,0,10686517,64652565,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@10,paid_equivalent_cache_miss,USD,11240,0.912811,0.907562,0.917972,10260.000000,112400,0,53966048,53966048,0,10686517,0,10686517,64652565,10.547471,10.547471,10.048120,0.001028,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5395879,5395879,0,1050976,0,1050976,6446855,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5395879,5395879,0,1050976,0,1050976,6446855,1.049696,1.049696,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,observed_free,USD,11240,0.643416,0.634520,0.652224,7232.000000,134880,11240,83597936,64765615,18832321,12803941,550760,13354701,96952637,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@12,paid_equivalent_cache_miss,USD,11240,0.643416,0.634520,0.652224,7232.000000,134880,11240,83597936,64765615,18832321,12803941,550760,13354701,96952637,15.443027,15.443027,14.711764,0.002135,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,observed_free,USD,11240,0.629270,0.620374,0.638167,7073.000000,134880,0,64765615,64765615,0,12803941,0,12803941,77569556,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@12,paid_equivalent_cache_miss,USD,11240,0.629270,0.620374,0.638167,7073.000000,134880,0,64765615,64765615,0,12803941,0,12803941,77569556,12.652290,12.652290,12.053175,0.001789,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,observed_free,USD,11240,0.933363,0.928737,0.937900,10491.000000,134880,0,64765615,64765615,0,12803941,0,12803941,77569556,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@12,paid_equivalent_cache_miss,USD,11240,0.933363,0.928737,0.937900,10491.000000,134880,0,64765615,64765615,0,12803941,0,12803941,77569556,12.652290,12.652290,12.053175,0.001206,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396061,5396061,0,1050921,0,1050921,6446982,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396061,5396061,0,1050921,0,1050921,6446982,1.049706,1.049706,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@14,observed_free,USD,11207,0.645936,0.637102,0.654769,7239.000000,156898,11207,96420146,75323418,21096728,14894113,638799,15532912,111953058,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@14,paid_equivalent_cache_miss,USD,11207,0.645936,0.637102,0.654769,7239.000000,156898,11207,96420146,75323418,21096728,14894113,638799,15532912,111953058,17.848036,17.848036,17.057049,0.002466,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@14,observed_free,USD,11207,0.638440,0.629517,0.647363,7155.000000,156898,0,75323418,75323418,0,14894113,0,14894113,90217531,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@14,paid_equivalent_cache_miss,USD,11207,0.638440,0.629517,0.647363,7155.000000,156898,0,75323418,75323418,0,14894113,0,14894113,90217531,14.715630,14.715630,14.063465,0.002057,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@14,observed_free,USD,11207,0.947265,0.943071,0.951370,10616.000000,156898,0,75323418,75323418,0,14894113,0,14894113,90217531,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@14,paid_equivalent_cache_miss,USD,11207,0.947265,0.943071,0.951370,10616.000000,156898,0,75323418,75323418,0,14894113,0,14894113,90217531,14.715630,14.715630,14.063465,0.001386,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11207,0.414295,0.405193,0.423396,4643.000000,11207,0,5378924,5378924,0,1047585,0,1047585,6426509,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11207,0.414295,0.405193,0.423396,4643.000000,11207,0,5378924,5378924,0,1047585,0,1047585,6426509,1.046373,1.046373,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@16,observed_free,USD,11241,0.648786,0.639979,0.657593,7293.000000,179856,0,86365379,86365379,0,17079852,0,17079852,103445231,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@16,paid_equivalent_cache_miss,USD,11241,0.648786,0.639979,0.657593,7293.000000,179856,0,86365379,86365379,0,17079852,0,17079852,103445231,16.873512,16.873512,16.073272,0.002314,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@16,observed_free,USD,11241,0.957744,0.954008,0.961391,10766.000000,179856,0,86365379,86365379,0,17079852,0,17079852,103445231,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@16,paid_equivalent_cache_miss,USD,11241,0.957744,0.954008,0.961391,10766.000000,179856,0,86365379,86365379,0,17079852,0,17079852,103445231,16.873512,16.873512,16.073272,0.001567,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,1.049787,1.049787,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@16,observed_free,USD,11241,0.645405,0.636509,0.654212,7255.000000,179856,11241,109861684,86365379,23496305,17079852,730665,17810517,127672201,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@16,paid_equivalent_cache_miss,USD,11241,0.645405,0.636509,0.654212,7255.000000,179856,11241,109861684,86365379,23496305,17079852,730665,17810517,127672201,20.367581,20.367581,19.401632,0.002807,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@2,observed_free,USD,11241,0.535095,0.525843,0.544347,6015.000000,22482,11241,17985074,10792846,7192228,2113500,123651,2237151,20222225,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@2,paid_equivalent_cache_miss,USD,11241,0.535095,0.525843,0.544347,6015.000000,22482,11241,17985074,10792846,7192228,2113500,123651,2237151,20222225,3.144313,3.144313,2.995191,0.000523,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@2,observed_free,USD,11241,0.399875,0.390802,0.408949,4495.000000,22482,0,10792846,10792846,0,2113500,0,2113500,12906346,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@2,paid_equivalent_cache_miss,USD,11241,0.399875,0.390802,0.408949,4495.000000,22482,0,10792846,10792846,0,2113500,0,2113500,12906346,2.102778,2.102778,2.003052,0.000468,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@2,observed_free,USD,11241,0.596121,0.587047,0.605195,6701.000000,22482,0,10792846,10792846,0,2113500,0,2113500,12906346,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@2,paid_equivalent_cache_miss,USD,11241,0.596121,0.587047,0.605195,6701.000000,22482,0,10792846,10792846,0,2113500,0,2113500,12906346,2.102778,2.102778,2.003052,0.000314,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,1.049787,1.049787,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,observed_free,USD,11241,0.615070,0.606085,0.624055,6914.000000,44964,11241,31113226,21586762,9526464,4259386,213579,4472965,35586191,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@4,paid_equivalent_cache_miss,USD,11241,0.615070,0.606085,0.624055,6914.000000,44964,11241,31113226,21586762,9526464,4259386,213579,4472965,35586191,5.608282,5.608282,5.342305,0.000811,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,observed_free,USD,11241,0.507339,0.498087,0.516591,5703.000000,44964,0,21586762,21586762,0,4259386,0,4259386,25846148,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@4,paid_equivalent_cache_miss,USD,11241,0.507339,0.498087,0.516591,5703.000000,44964,0,21586762,21586762,0,4259386,0,4259386,25846148,4.214775,4.214775,4.014886,0.000739,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,observed_free,USD,11241,0.765590,0.757762,0.773419,8606.000000,44964,0,21586762,21586762,0,4259386,0,4259386,25846148,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@4,paid_equivalent_cache_miss,USD,11241,0.765590,0.757762,0.773419,8606.000000,44964,0,21586762,21586762,0,4259386,0,4259386,25846148,4.214775,4.214775,4.014886,0.000490,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,1.049787,1.049787,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@6,observed_free,USD,11241,0.637043,0.628147,0.645939,7161.000000,67446,11241,44241153,32381287,11859866,6404414,292276,6696690,50937843,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@6,paid_equivalent_cache_miss,USD,11241,0.637043,0.628147,0.645939,7161.000000,67446,11241,44241153,32381287,11859866,6404414,292276,6696690,50937843,8.068835,8.068835,7.686164,0.001127,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@6,observed_free,USD,11241,0.573170,0.564007,0.582333,6443.000000,67446,0,32381287,32381287,0,6404414,0,6404414,38785701,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@6,paid_equivalent_cache_miss,USD,11241,0.573170,0.564007,0.582333,6443.000000,67446,0,32381287,32381287,0,6404414,0,6404414,38785701,6.326616,6.326616,6.026571,0.000982,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@6,observed_free,USD,11241,0.840584,0.833823,0.847345,9449.000000,67446,0,32381287,32381287,0,6404414,0,6404414,38785701,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@6,paid_equivalent_cache_miss,USD,11241,0.840584,0.833823,0.847345,9449.000000,67446,0,32381287,32381287,0,6404414,0,6404414,38785701,6.326616,6.326616,6.026571,0.000670,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,1.049787,1.049787,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@8,observed_free,USD,11241,0.606974,0.597901,0.615959,6823.000000,89928,0,43175896,43175896,0,8543869,0,8543869,51719765,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,majority@8,paid_equivalent_cache_miss,USD,11241,0.606974,0.597901,0.615959,6823.000000,89928,0,43175896,43175896,0,8543869,0,8543869,51719765,8.436909,8.436909,8.036782,0.001237,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@8,observed_free,USD,11241,0.884263,0.878303,0.890134,9940.000000,89928,0,43175896,43175896,0,8543869,0,8543869,51719765,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,oracle@8,paid_equivalent_cache_miss,USD,11241,0.884263,0.878303,0.890134,9940.000000,89928,0,43175896,43175896,0,8543869,0,8543869,51719765,8.436909,8.436909,8.036782,0.000849,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,observed_free,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,deepseek,deepseek_to_deepseek,single@1,paid_equivalent_cache_miss,USD,11241,0.414465,0.405391,0.423539,4659.000000,11241,0,5396325,5396325,0,1051078,0,1051078,6447403,1.049787,1.049787,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@8,observed_free,USD,11241,0.640512,0.631616,0.649408,7200.000000,89928,11241,57363425,43175896,14187529,8543869,1307253,9851122,67214547,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,deepseek,deepseek,deepseek_to_deepseek,rank@8,paid_equivalent_cache_miss,USD,11241,0.640512,0.631616,0.649408,7200.000000,89928,11241,57363425,43175896,14187529,8543869,1307253,9851122,67214547,10.789194,10.789194,10.277508,0.001498,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@10,observed_free,USD,11227,0.583059,0.573973,0.592144,6546.000000,112270,11227,70391505,53891218,16500287,10674005,460307,11134312,81525817,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@10,paid_equivalent_cache_miss,MIXED,11227,0.583059,0.573973,0.592144,6546.000000,112270,11227,70391505,53891218,16500287,10674005,460307,11134312,81525817,27.954393,12.936375,12.340407,0.001976,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@10,observed_free,USD,11227,0.624566,0.615570,0.633473,7012.000000,112270,0,53891218,53891218,0,10674005,0,10674005,64565223,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@10,paid_equivalent_cache_miss,MIXED,11227,0.624566,0.615570,0.633473,7012.000000,112270,0,53891218,53891218,0,10674005,0,10674005,64565223,10.533492,10.533492,10.048223,0.001502,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@10,observed_free,USD,11227,0.912800,0.907544,0.917966,10248.000000,112270,0,53891218,53891218,0,10674005,0,10674005,64565223,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@10,paid_equivalent_cache_miss,MIXED,11227,0.912800,0.907544,0.917966,10248.000000,112270,0,53891218,53891218,0,10674005,0,10674005,64565223,10.533492,10.533492,10.048223,0.001028,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11227,0.414358,0.405273,0.423443,4652.000000,11227,0,5388396,5388396,0,1049710,0,1049710,6438106,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11227,0.414358,0.405273,0.423443,4652.000000,11227,0,5388396,5388396,0,1049710,0,1049710,6438106,1.048294,1.048294,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,observed_free,USD,11067,0.590042,0.580916,0.599169,6530.000000,132804,11067,82328527,63786920,18541607,12604485,542283,13146768,95475295,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@12,paid_equivalent_cache_miss,MIXED,11067,0.590042,0.580916,0.599169,6530.000000,132804,11067,82328527,63786920,18541607,12604485,542283,13146768,95475295,32.085598,15.166483,14.672859,0.002323,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,observed_free,USD,11067,0.628083,0.619048,0.637119,6951.000000,132804,0,63786920,63786920,0,12604485,0,12604485,76391405,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@12,paid_equivalent_cache_miss,MIXED,11067,0.628083,0.619048,0.637119,6951.000000,132804,0,63786920,63786920,0,12604485,0,12604485,76391405,12.459425,12.459425,12.053907,0.001792,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,observed_free,USD,11067,0.932863,0.928165,0.937472,10324.000000,132804,0,63786920,63786920,0,12604485,0,12604485,76391405,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@12,paid_equivalent_cache_miss,MIXED,11067,0.932863,0.928165,0.937472,10324.000000,132804,0,63786920,63786920,0,12604485,0,12604485,76391405,12.459425,12.459425,12.053907,0.001207,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11067,0.414656,0.405530,0.423873,4589.000000,11067,0,5314521,5314521,0,1034318,0,1034318,6348839,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11067,0.414656,0.405530,0.423873,4589.000000,11067,0,5314521,5314521,0,1034318,0,1034318,6348839,1.033642,1.033642,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@14,observed_free,USD,11010,0.598002,0.588828,0.607175,6584.000000,154140,11010,94764279,74035599,20728680,14632502,627570,15260072,110024351,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@14,paid_equivalent_cache_miss,MIXED,11010,0.598002,0.588828,0.607175,6584.000000,154140,11010,94764279,74035599,20728680,14632502,627570,15260072,110024351,36.445904,17.494335,17.012010,0.002657,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@14,observed_free,USD,11010,0.639328,0.630336,0.648320,7039.000000,154140,0,74035599,74035599,0,14632502,0,14632502,88668101,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@14,paid_equivalent_cache_miss,MIXED,11010,0.639328,0.630336,0.648320,7039.000000,154140,0,74035599,74035599,0,14632502,0,14632502,88668101,14.462084,14.462084,14.063360,0.002055,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@14,observed_free,USD,11010,0.947502,0.943324,0.951589,10432.000000,154140,0,74035599,74035599,0,14632502,0,14632502,88668101,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@14,paid_equivalent_cache_miss,MIXED,11010,0.947502,0.943324,0.951589,10432.000000,154140,0,74035599,74035599,0,14632502,0,14632502,88668101,14.462084,14.462084,14.063360,0.001386,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11010,0.414078,0.404905,0.423252,4559.000000,11010,0,5286965,5286965,0,1029202,0,1029202,6316167,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11010,0.414078,0.404905,0.423252,4559.000000,11010,0,5286965,5286965,0,1029202,0,1029202,6316167,1.028352,1.028352,1.000000,0.000226,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@16,observed_free,USD,11240,0.648754,0.639947,0.657562,7292.000000,179840,0,86361651,86361651,0,17079105,0,17079105,103440756,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@16,paid_equivalent_cache_miss,MIXED,11240,0.648754,0.639947,0.657562,7292.000000,179840,0,86361651,86361651,0,17079105,0,17079105,103440756,16.872781,16.872781,16.073326,0.002314,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@16,observed_free,USD,11240,0.957740,0.954004,0.961388,10765.000000,179840,0,86361651,86361651,0,17079105,0,17079105,103440756,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@16,paid_equivalent_cache_miss,MIXED,11240,0.957740,0.954004,0.961388,10765.000000,179840,0,86361651,86361651,0,17079105,0,17079105,103440756,16.872781,16.872781,16.073326,0.001567,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396092,5396092,0,1051017,0,1051017,6447109,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396092,5396092,0,1051017,0,1051017,6447109,1.049738,1.049738,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@16,observed_free,USD,11240,0.598221,0.589146,0.607295,6724.000000,179840,11240,109856884,86361651,23495233,17079105,730600,17809705,127666589,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,deepseek,mimo,deepseek_to_mimo,rank@16,paid_equivalent_cache_miss,MIXED,11240,0.598221,0.589146,0.607295,6724.000000,179840,11240,109856884,86361651,23495233,17079105,730600,17809705,127666589,41.829214,20.315047,19.352493,0.003021,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@2,observed_free,USD,11239,0.513391,0.504137,0.522644,5770.000000,22478,11239,17980759,10790200,7190559,2113099,123629,2236728,20217487,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@2,paid_equivalent_cache_miss,MIXED,11239,0.513391,0.504137,0.522644,5770.000000,22478,11239,17980759,10790200,7190559,2113099,123629,2236728,20217487,9.540113,3.128202,2.980480,0.000542,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@2,observed_free,USD,11239,0.399947,0.390871,0.409022,4495.000000,22478,0,10790200,10790200,0,2113099,0,2113099,12903299,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@2,paid_equivalent_cache_miss,MIXED,11239,0.399947,0.390871,0.409022,4495.000000,22478,0,10790200,10790200,0,2113099,0,2113099,12903299,2.102296,2.102296,2.003020,0.000468,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@2,observed_free,USD,11239,0.596049,0.586974,0.605125,6699.000000,22478,0,10790200,10790200,0,2113099,0,2113099,12903299,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@2,paid_equivalent_cache_miss,MIXED,11239,0.596049,0.586974,0.605125,6699.000000,22478,0,10790200,10790200,0,2113099,0,2113099,12903299,2.102296,2.102296,2.003020,0.000314,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11239,0.414361,0.405285,0.423436,4657.000000,11239,0,5395002,5395002,0,1050938,0,1050938,6445940,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11239,0.414361,0.405285,0.423436,4657.000000,11239,0,5395002,5395002,0,1050938,0,1050938,6445940,1.049563,1.049563,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,observed_free,USD,11231,0.567269,0.558098,0.576440,6371.000000,44924,11231,31073450,21558304,9515146,4255071,213389,4468460,35541910,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@4,paid_equivalent_cache_miss,MIXED,11231,0.567269,0.558098,0.576440,6371.000000,44924,11231,31073450,21558304,9515146,4255071,213389,4468460,35541910,14.151506,5.580882,5.322821,0.000876,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,observed_free,USD,11231,0.507346,0.498086,0.516606,5698.000000,44924,0,21558304,21558304,0,4255071,0,4255071,25813375,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@4,paid_equivalent_cache_miss,MIXED,11231,0.507346,0.498086,0.516606,5698.000000,44924,0,21558304,21558304,0,4255071,0,4255071,25813375,4.209582,4.209582,4.014930,0.000739,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,observed_free,USD,11231,0.765649,0.757813,0.773484,8599.000000,44924,0,21558304,21558304,0,4255071,0,4255071,25813375,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@4,paid_equivalent_cache_miss,MIXED,11231,0.765649,0.757813,0.773484,8599.000000,44924,0,21558304,21558304,0,4255071,0,4255071,25813375,4.209582,4.209582,4.014930,0.000490,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11231,0.414389,0.405307,0.423471,4654.000000,11231,0,5389212,5389212,0,1049974,0,1049974,6439186,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11231,0.414389,0.405307,0.423471,4654.000000,11231,0,5389212,5389212,0,1049974,0,1049974,6439186,1.048482,1.048482,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@6,observed_free,USD,11230,0.577916,0.568744,0.587088,6490.000000,67380,11230,44193039,32345802,11847237,6397756,291980,6689736,50882775,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,deepseek,mimo,deepseek_to_mimo,rank@6,paid_equivalent_cache_miss,MIXED,11230,0.577916,0.568744,0.587088,6490.000000,67380,11230,44193039,32345802,11847237,6397756,291980,6689736,50882775,18.750981,8.034432,7.661603,0.001238,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@6,observed_free,USD,11230,0.573375,0.564203,0.582547,6439.000000,67380,0,32345802,32345802,0,6397756,0,6397756,38743558,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@6,paid_equivalent_cache_miss,MIXED,11230,0.573375,0.564203,0.582547,6439.000000,67380,0,32345802,32345802,0,6397756,0,6397756,38743558,6.319784,6.319784,6.026521,0.000981,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@6,observed_free,USD,11230,0.840695,0.833927,0.847462,9441.000000,67380,0,32345802,32345802,0,6397756,0,6397756,38743558,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@6,paid_equivalent_cache_miss,MIXED,11230,0.840695,0.833927,0.847462,9441.000000,67380,0,32345802,32345802,0,6397756,0,6397756,38743558,6.319784,6.319784,6.026521,0.000669,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11230,0.414426,0.405343,0.423508,4654.000000,11230,0,5390412,5390412,0,1050016,0,1050016,6440428,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11230,0.414426,0.405343,0.423508,4654.000000,11230,0,5390412,5390412,0,1050016,0,1050016,6440428,1.048662,1.048662,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@8,observed_free,USD,11240,0.606940,0.597865,0.615925,6822.000000,89920,0,43174032,43174032,0,8543470,0,8543470,51717502,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,majority@8,paid_equivalent_cache_miss,MIXED,11240,0.606940,0.597865,0.615925,6822.000000,89920,0,43174032,43174032,0,8543470,0,8543470,51717502,8.436536,8.436536,8.036802,0.001237,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@8,observed_free,USD,11240,0.884253,0.878292,0.890125,9939.000000,89920,0,43174032,43174032,0,8543470,0,8543470,51717502,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,oracle@8,paid_equivalent_cache_miss,MIXED,11240,0.884253,0.878292,0.890125,9939.000000,89920,0,43174032,43174032,0,8543470,0,8543470,51717502,8.436536,8.436536,8.036802,0.000849,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,observed_free,USD,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396092,5396092,0,1051017,0,1051017,6447109,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,deepseek,mimo,deepseek_to_mimo,single@1,paid_equivalent_cache_miss,MIXED,11240,0.414502,0.405427,0.423577,4659.000000,11240,0,5396092,5396092,0,1051017,0,1051017,6447109,1.049738,1.049738,1.000000,0.000225,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,deepseek,mimo,deepseek_to_mimo,rank@8,observed_free,USD,11240,0.594395,0.585320,0.603470,6681.000000,89920,11240,57360907,43174032,14186875,8543470,1306501,9849971,67210878,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,deepseek,mimo,deepseek_to_mimo,rank@8,paid_equivalent_cache_miss,MIXED,11240,0.594395,0.585320,0.603470,6681.000000,89920,11240,57360907,43174032,14186875,8543470,1306501,9849971,67210878,25.236413,10.753760,10.244232,0.001610,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@10,observed_free,USD,11241,0.588916,0.579842,0.597990,6620.000000,112410,11241,80192418,53963391,26229027,20394512,460881,20855393,101047811,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@10,paid_equivalent_cache_miss,MIXED,11241,0.588916,0.579842,0.597990,6620.000000,112410,11241,80192418,53963391,26229027,20394512,460881,20855393,101047811,98.553525,16.870409,13.087200,0.002548,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@10,observed_free,USD,11241,0.202028,0.194645,0.209501,2271.000000,112410,0,53963391,53963391,0,20394512,0,20394512,74357903,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@10,paid_equivalent_cache_miss,MIXED,11241,0.202028,0.194645,0.209501,2271.000000,112410,0,53963391,53963391,0,20394512,0,20394512,74357903,94.752415,13.069299,10.138494,0.005755,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@10,observed_free,USD,11241,0.988969,0.987012,0.990837,11117.000000,112410,0,53963391,53963391,0,20394512,0,20394512,74357903,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@10,paid_equivalent_cache_miss,MIXED,11241,0.988969,0.987012,0.990837,11117.000000,112410,0,53963391,53963391,0,20394512,0,20394512,74357903,94.752415,13.069299,10.138494,0.001176,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,observed_free,USD,11224,0.579116,0.569939,0.588204,6500.000000,134688,11224,95073400,64651572,30421828,24403634,549976,24953610,120027010,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@12,paid_equivalent_cache_miss,MIXED,11224,0.579116,0.569939,0.588204,6500.000000,134688,11224,95073400,64651572,30421828,24403634,549976,24953610,120027010,117.871889,20.062544,15.590829,0.003087,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,observed_free,USD,11224,0.187990,0.180773,0.195207,2110.000000,134688,0,64651572,64651572,0,24403634,0,24403634,89055206,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@12,paid_equivalent_cache_miss,MIXED,11224,0.187990,0.180773,0.195207,2110.000000,134688,0,64651572,64651572,0,24403634,0,24403634,89055206,113.458840,15.649495,12.161399,0.007417,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,observed_free,USD,11224,0.991536,0.989843,0.993229,11129.000000,134688,0,64651572,64651572,0,24403634,0,24403634,89055206,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@12,paid_equivalent_cache_miss,MIXED,11224,0.991536,0.989843,0.993229,11129.000000,134688,0,64651572,64651572,0,24403634,0,24403634,89055206,113.458840,15.649495,12.161399,0.001406,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11224,0.162865,0.156094,0.169726,1828.000000,11224,0,5387102,5387102,0,1971161,0,1971161,7358263,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11224,0.162865,0.156094,0.169726,1828.000000,11224,0,5387102,5387102,0,1971161,0,1971161,7358263,9.329424,1.286817,1.000000,0.000704,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@14,observed_free,USD,11127,0.579401,0.570235,0.588568,6447.000000,155778,11127,108998201,74588386,34409815,28265425,634239,28899664,137897865,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@14,paid_equivalent_cache_miss,MIXED,11127,0.579401,0.570235,0.588568,6447.000000,155778,11127,108998201,74588386,34409815,28265425,634239,28899664,137897865,136.114197,23.080373,18.114841,0.003580,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@14,observed_free,USD,11127,0.194931,0.187562,0.202301,2169.000000,155778,0,74588386,74588386,0,28265425,0,28265425,102853811,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@14,paid_equivalent_cache_miss,MIXED,11127,0.194931,0.187562,0.202301,2169.000000,155778,0,74588386,74588386,0,28265425,0,28265425,102853811,131.119236,18.085412,14.194501,0.008338,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@14,observed_free,USD,11127,0.993529,0.992001,0.994967,11055.000000,155778,0,74588386,74588386,0,28265425,0,28265425,102853811,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@14,paid_equivalent_cache_miss,MIXED,11127,0.993529,0.992001,0.994967,11055.000000,155778,0,74588386,74588386,0,28265425,0,28265425,102853811,131.119236,18.085412,14.194501,0.001636,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11127,0.162308,0.155478,0.169228,1806.000000,11127,0,5326886,5326886,0,1955219,0,1955219,7282105,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11127,0.162308,0.155478,0.169228,1806.000000,11127,0,5326886,5326886,0,1955219,0,1955219,7282105,9.237324,1.274114,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@16,observed_free,USD,11241,0.202829,0.195445,0.210302,2280.000000,179856,0,86358187,86358187,0,32627518,0,32627518,118985705,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@16,paid_equivalent_cache_miss,MIXED,11241,0.202829,0.195445,0.210302,2280.000000,179856,0,86358187,86358187,0,32627518,0,32627518,118985705,151.613223,20.912169,16.222591,0.009172,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@16,observed_free,USD,11241,0.994662,0.993239,0.995997,11181.000000,179856,0,86358187,86358187,0,32627518,0,32627518,118985705,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@16,paid_equivalent_cache_miss,MIXED,11241,0.994662,0.993239,0.995997,11181.000000,179856,0,86358187,86358187,0,32627518,0,32627518,118985705,151.613223,20.912169,16.222591,0.001870,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@16,observed_free,USD,11241,0.577262,0.568099,0.586425,6489.000000,179856,11241,125401856,86358187,39043669,32627518,730665,33358183,158760039,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,mimo,deepseek,mimo_to_deepseek,rank@16,paid_equivalent_cache_miss,MIXED,11241,0.577262,0.568099,0.586425,6489.000000,179856,11241,125401856,86358187,39043669,32627518,730665,33358183,158760039,157.283923,26.582869,20.621630,0.004097,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@2,observed_free,USD,11241,0.257272,0.249177,0.265368,2892.000000,22482,11241,19828832,10792562,9036270,3957535,123651,4081186,23910018,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@2,paid_equivalent_cache_miss,MIXED,11241,0.257272,0.249177,0.265368,2892.000000,22482,11241,19828832,10792562,9036270,3957535,123651,4081186,23910018,20.007332,3.880063,3.009954,0.001342,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@2,observed_free,USD,11241,0.153189,0.146517,0.159861,1722.000000,22482,0,10792562,10792562,0,3957535,0,3957535,14750097,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@2,paid_equivalent_cache_miss,MIXED,11241,0.153189,0.146517,0.159861,1722.000000,22482,0,10792562,10792562,0,3957535,0,3957535,14750097,18.707632,2.580363,2.001714,0.001498,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@2,observed_free,USD,11241,0.304065,0.295614,0.312606,3418.000000,22482,0,10792562,10792562,0,3957535,0,3957535,14750097,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@2,paid_equivalent_cache_miss,MIXED,11241,0.304065,0.295614,0.312606,3418.000000,22482,0,10792562,10792562,0,3957535,0,3957535,14750097,18.707632,2.580363,2.001714,0.000755,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,observed_free,USD,11241,0.388133,0.379148,0.397118,4363.000000,44964,11241,34927613,21585217,13342396,8075435,213579,8289014,43216627,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@4,paid_equivalent_cache_miss,MIXED,11241,0.388133,0.379148,0.397118,4363.000000,44964,11241,34927613,21585217,13342396,8075435,213579,8289014,43216627,39.663825,7.132715,5.533195,0.001635,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,observed_free,USD,11241,0.155947,0.149275,0.162708,1753.000000,44964,0,21585217,21585217,0,8075435,0,8075435,29660652,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@4,paid_equivalent_cache_miss,MIXED,11241,0.155947,0.149275,0.162708,1753.000000,44964,0,21585217,21585217,0,8075435,0,8075435,29660652,37.736087,5.204978,4.037756,0.002969,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,observed_free,USD,11241,0.537497,0.528245,0.546749,6042.000000,44964,0,21585217,21585217,0,8075435,0,8075435,29660652,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@4,paid_equivalent_cache_miss,MIXED,11241,0.537497,0.528245,0.546749,6042.000000,44964,0,21585217,21585217,0,8075435,0,8075435,29660652,37.736087,5.204978,4.037756,0.000861,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@6,observed_free,USD,11241,0.470599,0.461347,0.479851,5290.000000,67446,11241,50027521,32377939,17649582,12194382,292266,12486648,62514169,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,mimo,deepseek,mimo_to_deepseek,rank@6,paid_equivalent_cache_miss,MIXED,11241,0.470599,0.461347,0.479851,5290.000000,67446,11241,50027521,32377939,17649582,12194382,292266,12486648,62514169,59.319479,10.382666,8.054341,0.001963,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@6,observed_free,USD,11241,0.164131,0.157281,0.170981,1845.000000,67446,0,32377939,32377939,0,12194382,0,12194382,44572321,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@6,paid_equivalent_cache_miss,MIXED,11241,0.164131,0.157281,0.170981,1845.000000,67446,0,32377939,32377939,0,12194382,0,12194382,44572321,56.766703,7.829890,6.074028,0.004244,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@6,observed_free,USD,11241,0.707588,0.699137,0.715951,7954.000000,67446,0,32377939,32377939,0,12194382,0,12194382,44572321,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@6,paid_equivalent_cache_miss,MIXED,11241,0.707588,0.699137,0.715951,7954.000000,67446,0,32377939,32377939,0,12194382,0,12194382,44572321,56.766703,7.829890,6.074028,0.000984,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@8,observed_free,USD,11241,0.175607,0.168579,0.182635,1974.000000,89928,0,43170665,43170665,0,16284228,0,16284228,59454893,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,majority@8,paid_equivalent_cache_miss,MIXED,11241,0.175607,0.168579,0.182635,1974.000000,89928,0,43170665,43170665,0,16284228,0,16284228,59454893,75.739121,10.446775,8.104074,0.005292,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@8,observed_free,USD,11241,0.859265,0.852771,0.865670,9659.000000,89928,0,43170665,43170665,0,16284228,0,16284228,59454893,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,oracle@8,paid_equivalent_cache_miss,MIXED,11241,0.859265,0.852771,0.865670,9659.000000,89928,0,43170665,43170665,0,16284228,0,16284228,59454893,75.739121,10.446775,8.104074,0.001082,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,observed_free,USD,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,deepseek,mimo_to_deepseek,single@1,paid_equivalent_cache_miss,MIXED,11241,0.162619,0.155858,0.169469,1828.000000,11241,0,5396274,5396274,0,1974766,0,1974766,7371040,9.345806,1.289077,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,mimo,deepseek,mimo_to_deepseek,rank@8,observed_free,USD,11241,0.532871,0.523619,0.542123,5990.000000,89928,11241,65098309,43170665,21927644,16284228,1217295,17501523,82599832,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,mimo,deepseek,mimo_to_deepseek,rank@8,paid_equivalent_cache_miss,MIXED,11241,0.532871,0.523619,0.542123,5990.000000,89928,11241,65098309,43170665,21927644,16284228,1217295,17501523,82599832,79.149834,13.857488,10.749930,0.002313,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,mimo,mimo,mimo_to_mimo,rank@10,observed_free,USD,11229,0.499955,0.490694,0.509217,5614.000000,112290,11229,80115937,53910851,26205086,20376291,460389,20836680,100952617,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,live,__global__,mimo,mimo,mimo_to_mimo,rank@10,paid_equivalent_cache_miss,CNY,11229,0.499955,0.490694,0.509217,5614.000000,112290,11229,80115937,53910851,26205086,20376291,460389,20836680,100952617,121.789297,16.798524,13.044368,0.002992,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@10,observed_free,USD,11229,0.201799,0.194407,0.209280,2266.000000,112290,0,53910851,53910851,0,20376291,0,20376291,74287142,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@10,paid_equivalent_cache_miss,CNY,11229,0.201799,0.194407,0.209280,2266.000000,112290,0,53910851,53910851,0,20376291,0,20376291,74287142,94.663433,13.057025,10.139024,0.005762,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@10,observed_free,USD,11229,0.989046,0.987087,0.990916,11106.000000,112290,0,53910851,53910851,0,20376291,0,20376291,74287142,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@10,paid_equivalent_cache_miss,CNY,11229,0.989046,0.987087,0.990916,11106.000000,112290,0,53910851,53910851,0,20376291,0,20376291,74287142,94.663433,13.057025,10.139024,0.001176,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11229,0.162526,0.155757,0.169383,1825.000000,11229,0,5391020,5391020,0,1972763,0,1972763,7363783,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11229,0.162526,0.155757,0.169383,1825.000000,11229,0,5391020,5391020,0,1972763,0,1972763,7363783,9.336546,1.287799,1.000000,0.000706,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,mimo,mimo,mimo_to_mimo,rank@12,observed_free,USD,11091,0.498783,0.489496,0.508070,5532.000000,133092,11091,93975674,63923096,30052578,24102556,543459,24646015,118621689,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,live,__global__,mimo,mimo,mimo_to_mimo,rank@12,paid_equivalent_cache_miss,CNY,11091,0.498783,0.489496,0.508070,5532.000000,133092,11091,93975674,63923096,30052578,24102556,543459,24646015,118621689,143.267704,19.761063,15.540130,0.003572,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,observed_free,USD,11091,0.188712,0.181499,0.196015,2093.000000,133092,0,63923096,63923096,0,24102556,0,24102556,88025652,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@12,paid_equivalent_cache_miss,CNY,11091,0.188712,0.181499,0.196015,2093.000000,133092,0,63923096,63923096,0,24102556,0,24102556,88025652,112.128208,15.465960,12.162455,0.007389,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,observed_free,USD,11091,0.991434,0.989721,0.993148,10996.000000,133092,0,63923096,63923096,0,24102556,0,24102556,88025652,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@12,paid_equivalent_cache_miss,CNY,11091,0.991434,0.989721,0.993148,10996.000000,133092,0,63923096,63923096,0,24102556,0,24102556,88025652,112.128208,15.465960,12.162455,0.001407,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11091,0.163466,0.156613,0.170408,1813.000000,11091,0,5326402,5326402,0,1946405,0,1946405,7272807,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11091,0.163466,0.156613,0.170408,1813.000000,11091,0,5326402,5326402,0,1946405,0,1946405,7272807,9.219212,1.271615,1.000000,0.000701,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,mimo,mimo,mimo_to_mimo,rank@14,observed_free,USD,11219,0.500758,0.491488,0.510028,5618.000000,157066,11219,110149134,75432391,34716743,28505316,639483,29144799,139293933,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,live,__global__,mimo,mimo,mimo_to_mimo,rank@14,paid_equivalent_cache_miss,CNY,11219,0.500758,0.491488,0.510028,5618.000000,157066,11219,110149134,75432391,34716743,28505316,639483,29144799,139293933,168.438732,23.232929,18.054950,0.004135,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@14,observed_free,USD,11219,0.194937,0.187628,0.202335,2187.000000,157066,0,75432391,75432391,0,28505316,0,28505316,103937707,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@14,paid_equivalent_cache_miss,CNY,11219,0.194937,0.187628,0.202335,2187.000000,157066,0,75432391,75432391,0,28505316,0,28505316,103937707,132.443023,18.268003,14.196569,0.008353,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@14,observed_free,USD,11219,0.993582,0.992067,0.995008,11147.000000,157066,0,75432391,75432391,0,28505316,0,28505316,103937707,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@14,paid_equivalent_cache_miss,CNY,11219,0.993582,0.992067,0.995008,11147.000000,157066,0,75432391,75432391,0,28505316,0,28505316,103937707,132.443023,18.268003,14.196569,0.001639,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11219,0.162849,0.156075,0.169712,1827.000000,11219,0,5387167,5387167,0,1971029,0,1971029,7358196,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11219,0.162849,0.156075,0.169712,1827.000000,11219,0,5387167,5387167,0,1971029,0,1971029,7358196,9.329225,1.286790,1.000000,0.000704,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@16,observed_free,USD,11240,0.202847,0.195463,0.210320,2280.000000,179840,0,86347931,86347931,0,32624723,0,32624723,118972654,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@16,paid_equivalent_cache_miss,CNY,11240,0.202847,0.195463,0.210320,2280.000000,179840,0,86347931,86347931,0,32624723,0,32624723,118972654,151.597377,20.909983,16.222594,0.009171,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@16,observed_free,USD,11240,0.994662,0.993238,0.995996,11180.000000,179840,0,86347931,86347931,0,32624723,0,32624723,118972654,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@16,paid_equivalent_cache_miss,CNY,11240,0.994662,0.993238,0.995996,11180.000000,179840,0,86347931,86347931,0,32624723,0,32624723,118972654,151.597377,20.909983,16.222594,0.001870,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11240,0.162633,0.155872,0.169484,1828.000000,11240,0,5395633,5395633,0,1974599,0,1974599,7370232,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11240,0.162633,0.155872,0.169484,1828.000000,11240,0,5395633,5395633,0,1974599,0,1974599,7370232,9.344831,1.288942,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,mimo,mimo,mimo_to_mimo,rank@16,observed_free,USD,11240,0.508452,0.499199,0.517705,5715.000000,179840,11240,125388076,86347931,39040145,32624723,730600,33355323,158743399,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,reused_rank16_live,__global__,mimo,mimo,mimo_to_mimo,rank@16,paid_equivalent_cache_miss,CNY,11240,0.508452,0.499199,0.517705,5715.000000,179840,11240,125388076,86347931,39040145,32624723,730600,33355323,158743399,192.098722,26.496375,20.556685,0.004636,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,mimo,mimo,mimo_to_mimo,rank@2,observed_free,USD,11238,0.243460,0.235540,0.251379,2736.000000,22476,11238,19822505,10789040,9033465,3956407,123618,4080025,23902530,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,live,__global__,mimo,mimo,mimo_to_mimo,rank@2,paid_equivalent_cache_miss,CNY,11238,0.243460,0.235540,0.251379,2736.000000,22476,11238,19822505,10789040,9033465,3956407,123618,4080025,23902530,27.982555,3.859663,2.995040,0.001411,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@2,observed_free,USD,11238,0.153230,0.146556,0.159904,1722.000000,22476,0,10789040,10789040,0,3956407,0,3956407,14745447,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@2,paid_equivalent_cache_miss,CNY,11238,0.153230,0.146556,0.159904,1722.000000,22476,0,10789040,10789040,0,3956407,0,3956407,14745447,18.701854,2.579566,2.001704,0.001498,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@2,observed_free,USD,11238,0.304147,0.295693,0.312689,3418.000000,22476,0,10789040,10789040,0,3956407,0,3956407,14745447,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@2,paid_equivalent_cache_miss,CNY,11238,0.304147,0.295693,0.312689,3418.000000,22476,0,10789040,10789040,0,3956407,0,3956407,14745447,18.701854,2.579566,2.001704,0.000755,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11238,0.162662,0.155900,0.169514,1828.000000,11238,0,5394513,5394513,0,1974228,0,1974228,7368741,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11238,0.162662,0.155900,0.169514,1828.000000,11238,0,5394513,5394513,0,1974228,0,1974228,7368741,9.342969,1.288685,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,mimo,mimo,mimo_to_mimo,rank@4,observed_free,USD,11233,0.347636,0.338823,0.356450,3905.000000,44932,11233,34898613,21566181,13332432,8070134,213427,8283561,43182174,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,live,__global__,mimo,mimo,mimo_to_mimo,rank@4,paid_equivalent_cache_miss,CNY,11233,0.347636,0.338823,0.356450,3905.000000,44932,11233,34898613,21566181,13332432,8070134,213427,8283561,43182174,51.465735,7.098722,5.511490,0.001818,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,observed_free,USD,11233,0.155791,0.149114,0.162557,1750.000000,44932,0,21566181,21566181,0,8070134,0,8070134,29636315,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@4,paid_equivalent_cache_miss,CNY,11233,0.155791,0.149114,0.162557,1750.000000,44932,0,21566181,21566181,0,8070134,0,8070134,29636315,37.706449,5.200890,4.038002,0.002972,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,observed_free,USD,11233,0.537523,0.528265,0.546782,6038.000000,44932,0,21566181,21566181,0,8070134,0,8070134,29636315,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@4,paid_equivalent_cache_miss,CNY,11233,0.537523,0.528265,0.546782,6038.000000,44932,0,21566181,21566181,0,8070134,0,8070134,29636315,37.706449,5.200890,4.038002,0.000861,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11233,0.162646,0.155880,0.169501,1827.000000,11233,0,5391515,5391515,0,1973190,0,1973190,7364705,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11233,0.162646,0.155880,0.169501,1827.000000,11233,0,5391515,5391515,0,1973190,0,1973190,7364705,9.337895,1.287986,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,mimo,mimo,mimo_to_mimo,rank@6,observed_free,USD,11237,0.421732,0.412566,0.430898,4739.000000,67422,11237,50011020,32366713,17644307,12191001,292162,12483163,62494183,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,live,__global__,mimo,mimo,mimo_to_mimo,rank@6,paid_equivalent_cache_miss,CNY,11237,0.421732,0.412566,0.430898,4739.000000,67422,11237,50011020,32366713,17644307,12191001,292162,12483163,62494183,74.977346,10.341703,8.025042,0.002182,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@6,observed_free,USD,11237,0.164190,0.157337,0.171042,1845.000000,67422,0,32366713,32366713,0,12191001,0,12191001,44557714,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@6,paid_equivalent_cache_miss,CNY,11237,0.164190,0.157337,0.171042,1845.000000,67422,0,32366713,32366713,0,12191001,0,12191001,44557714,56.748715,7.827409,6.073979,0.004242,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@6,observed_free,USD,11237,0.707662,0.699208,0.716027,7952.000000,67422,0,32366713,32366713,0,12191001,0,12191001,44557714,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@6,paid_equivalent_cache_miss,CNY,11237,0.707662,0.699208,0.716027,7952.000000,67422,0,32366713,32366713,0,12191001,0,12191001,44557714,56.748715,7.827409,6.073979,0.000984,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11237,0.162677,0.155914,0.169529,1828.000000,11237,0,5394403,5394403,0,1974260,0,1974260,7368663,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11237,0.162677,0.155914,0.169529,1828.000000,11237,0,5394403,5394403,0,1974260,0,1974260,7368663,9.342923,1.288679,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@8,observed_free,USD,11240,0.175623,0.168594,0.182651,1974.000000,89920,0,43165537,43165537,0,16282830,0,16282830,59448367,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,majority@8,paid_equivalent_cache_miss,CNY,11240,0.175623,0.168594,0.182651,1974.000000,89920,0,43165537,43165537,0,16282830,0,16282830,59448367,75.731197,10.445682,8.104075,0.005292,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@8,observed_free,USD,11240,0.859342,0.852847,0.865747,9659.000000,89920,0,43165537,43165537,0,16282830,0,16282830,59448367,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,oracle@8,paid_equivalent_cache_miss,CNY,11240,0.859342,0.852847,0.865747,9659.000000,89920,0,43165537,43165537,0,16282830,0,16282830,59448367,75.731197,10.445682,8.104075,0.001081,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,observed_free,USD,11240,0.162633,0.155872,0.169484,1828.000000,11240,0,5395633,5395633,0,1974599,0,1974599,7370232,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,no_selector,__global__,mimo,mimo,mimo_to_mimo,single@1,paid_equivalent_cache_miss,CNY,11240,0.162633,0.155872,0.169484,1828.000000,11240,0,5395633,5395633,0,1974599,0,1974599,7370232,9.344831,1.288942,1.000000,0.000705,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,mimo,mimo,mimo_to_mimo,rank@8,observed_free,USD,11240,0.473577,0.464324,0.482829,5323.000000,89920,11240,65091121,43165537,21925584,16282830,1217328,17500158,82591279,0.000000,0.000000,,0.000000,estimated
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,reused_rank16_truncated,__global__,mimo,mimo,mimo_to_mimo,rank@8,paid_equivalent_cache_miss,CNY,11240,0.473577,0.464324,0.482829,5323.000000,89920,11240,65091121,43165537,21925584,16282830,1217328,17500158,82591279,100.091437,13.805715,10.710889,0.002594,estimated

data/external/evidence/formal/five_benchmark_cost_efficiency/natural_pool_size_incremental_cost_effectiveness.csv

@@ -0,0 +1,385 @@
+experiment_id,population,pool_size,benchmark,generator,selector,cell_id,cost_scenario,strategy_a,strategy_b,delta_accuracy,delta_correct_questions,delta_cost_usd_normalized,incremental_cost_per_extra_correct
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@10,single@1,0.210320,2364.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@10,majority@10,0.021441,241.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@10,majority@10,0.287989,3237.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@10,single@1,0.231761,2605.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@12,single@1,0.214768,2414.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@12,majority@12,0.014146,159.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@12,majority@12,0.304093,3418.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@12,single@1,0.228914,2573.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@14,single@1,0.224145,2512.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@14,majority@14,0.007496,84.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@14,majority@14,0.308825,3461.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@14,single@1,0.231641,2596.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@16,single@1,0.234321,2634.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@16,majority@16,-0.003381,-38.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@16,majority@16,0.308958,3473.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@16,single@1,0.230940,2596.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@2,single@1,-0.014590,-164.000000,0.000000,
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@2,majority@2,0.135220,1520.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@2,majority@2,0.196246,2206.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@2,single@1,0.120630,1356.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@4,single@1,0.092874,1044.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@4,majority@4,0.107731,1211.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@4,majority@4,0.258251,2903.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@4,single@1,0.200605,2255.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@6,single@1,0.158705,1784.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@6,majority@6,0.063873,718.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@6,majority@6,0.267414,3006.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@6,single@1,0.222578,2502.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,majority@8,single@1,0.192509,2164.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@8,majority@8,0.033538,377.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,oracle@8,majority@8,0.277289,3117.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,observed_free,rank@8,single@1,0.226047,2541.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@10,single@1,0.210320,2364.000000,2.833948,0.001199
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@10,majority@10,0.021441,241.000000,0.175293,0.000727
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@10,majority@10,0.287989,3237.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,10,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@10,single@1,0.231761,2605.000000,3.009241,0.001155
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@12,single@1,0.214768,2414.000000,3.457080,0.001432
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@12,majority@12,0.014146,159.000000,0.206944,0.001302
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@12,majority@12,0.304093,3418.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,12,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@12,single@1,0.228914,2573.000000,3.664024,0.001424
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@14,single@1,0.224145,2512.000000,4.072872,0.001621
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@14,majority@14,0.007496,84.000000,0.237935,0.002833
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@14,majority@14,0.308825,3461.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,14,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@14,single@1,0.231641,2596.000000,4.310807,0.001661
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@16,single@1,0.234321,2634.000000,4.714770,0.001790
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@16,majority@16,-0.003381,-38.000000,0.270375,
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@16,majority@16,0.308958,3473.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,16,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@16,single@1,0.230940,2596.000000,4.985145,0.001920
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@2,single@1,-0.014590,-164.000000,0.312588,
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@2,majority@2,0.135220,1520.000000,0.054760,0.000036
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@2,majority@2,0.196246,2206.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,2,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@2,single@1,0.120630,1356.000000,0.367348,0.000271
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@4,single@1,0.092874,1044.000000,0.943659,0.000904
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@4,majority@4,0.107731,1211.000000,0.086476,0.000071
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@4,majority@4,0.258251,2903.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,4,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@4,single@1,0.200605,2255.000000,1.030135,0.000457
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@6,single@1,0.158705,1784.000000,1.574492,0.000883
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@6,majority@6,0.063873,718.000000,0.115044,0.000160
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@6,majority@6,0.267414,3006.000000,0.000000,0.000000
+cost_efficiency_pool_size_2x2_pilot,strict_common,6,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@6,single@1,0.222578,2502.000000,1.689536,0.000675
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,majority@8,single@1,0.192509,2164.000000,2.203764,0.001018
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,rank@8,majority@8,0.033538,377.000000,0.405756,0.001076
+cost_efficiency_pool_size_2x2_pilot,strict_common,8,__global__,deepseek,deepseek,deepseek_to_deepseek,paid_equivalent_cache_hit,oracle@8,majority@8,0.277289,3117.000000,0.000000,0.000000
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data/external/evidence/formal/five_benchmark_cost_efficiency/price_model.csv

@@ -0,0 +1,5 @@
+provider,model_price_row,currency,input_cache_hit_per_mtok,input_cache_miss_per_mtok,output_per_mtok,use,source_url,cny_per_usd
+deepseek,deepseek-v4-flash,USD,0.0028,0.14,0.28,DeepSeek generator/selector paid-equivalent,https://api-docs.deepseek.com/quick_start/pricing,7.25
+mimo,MiMo-V2.5,CNY,0.02,1.0,2.0,Mimo generator/selector paid-equivalent,https://mimo.mi.com/,7.25
+mimo_medium,MiMo-V2.5 medium-thinking,CNY,0.02,1.0,2.0,Mimo medium-thinking generator/selector paid-equivalent,https://mimo.mi.com/,7.25
+observed_free,free_or_local_endpoint,USD,0.0,0.0,0.0,Actual free/local endpoint scenario,,7.25

data/external/evidence/formal/five_benchmark_cost_efficiency/raw_log_consistency_audit.csv

@@ -0,0 +1,53 @@
+experiment_id,source_class,judge,generator,population,cell_id,n_tasks,n_details,n_parse_ok,n_failed,parse_ok_rate,bad_jsonl,duplicate_task_keys,duplicate_detail_keys,denominator_mismatch,failed_rows_with_nonempty_ranking,parse_ok_ranking_permutation_issues,raw_success_missing_from_details,status
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k12_3c9w,deepseek_to_deepseek,1774,1774,1769,5,0.997182,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k12_6c6w,deepseek_to_deepseek,1898,1898,1895,3,0.998419,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k12_9c3w,deepseek_to_deepseek,1491,1491,1487,4,0.997317,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k4_1c3w,deepseek_to_deepseek,2136,2136,2104,32,0.985019,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k4_2c2w,deepseek_to_deepseek,2147,2147,2124,23,0.989287,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,balanced_k4_3c1w,deepseek_to_deepseek,2135,2135,2135,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k10,deepseek_to_deepseek,11241,11241,11240,1,0.999911,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k12,deepseek_to_deepseek,11241,11241,11240,1,0.999911,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k14,deepseek_to_deepseek,11241,11241,11207,34,0.996975,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,reused_rank16_source,deepseek_judge,deepseek,strict_common_natural_k16,deepseek_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k2,deepseek_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k4,deepseek_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,deepseek,strict_common_natural_k6,deepseek_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k12_3c9w,mimo_to_deepseek,1608,1608,1601,7,0.995647,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k12_6c6w,mimo_to_deepseek,722,722,721,1,0.998615,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k12_9c3w,mimo_to_deepseek,23,23,23,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k4_1c3w,mimo_to_deepseek,2178,2178,2132,46,0.978880,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k4_2c2w,mimo_to_deepseek,2178,2178,2162,16,0.992654,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,balanced_k4_3c1w,mimo_to_deepseek,1624,1624,1624,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k10,mimo_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k12,mimo_to_deepseek,11241,11241,11224,17,0.998488,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k14,mimo_to_deepseek,11241,11241,11127,114,0.989859,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,reused_rank16_source,deepseek_judge,mimo,strict_common_natural_k16,mimo_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k2,mimo_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k4,mimo_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,deepseek_judge,mimo,strict_common_natural_k6,mimo_to_deepseek,11241,11241,11241,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k12_3c9w,deepseek_to_mimo,1774,1774,1708,66,0.962796,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k12_6c6w,deepseek_to_mimo,1898,1898,1880,18,0.990516,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k12_9c3w,deepseek_to_mimo,1491,1491,1473,18,0.987928,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k4_1c3w,deepseek_to_mimo,2136,2136,2135,1,0.999532,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k4_2c2w,deepseek_to_mimo,2147,2147,2126,21,0.990219,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,balanced_k4_3c1w,deepseek_to_mimo,2135,2135,2126,9,0.995785,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k10,deepseek_to_mimo,11241,11241,11227,14,0.998755,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k12,deepseek_to_mimo,11241,11241,11067,174,0.984521,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k14,deepseek_to_mimo,11241,11241,11010,231,0.979450,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,reused_rank16_source,mimo_judge,deepseek,strict_common_natural_k16,deepseek_to_mimo,11241,11241,11240,1,0.999911,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k2,deepseek_to_mimo,11241,11241,11239,2,0.999822,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k4,deepseek_to_mimo,11241,11241,11231,10,0.999110,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,deepseek,strict_common_natural_k6,deepseek_to_mimo,11241,11241,11230,11,0.999021,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k12_3c9w,mimo_to_mimo,1608,1608,1595,13,0.991915,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k12_6c6w,mimo_to_mimo,722,722,708,14,0.980609,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k12_9c3w,mimo_to_mimo,23,23,23,0,1.000000,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k4_1c3w,mimo_to_mimo,2178,2178,2137,41,0.981175,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k4_2c2w,mimo_to_mimo,2178,2178,2174,4,0.998163,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,balanced_k4_3c1w,mimo_to_mimo,1624,1624,1618,6,0.996305,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k10,mimo_to_mimo,11241,11241,11229,12,0.998932,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k12,mimo_to_mimo,11241,11241,11091,150,0.986656,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k14,mimo_to_mimo,11241,11241,11219,22,0.998043,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,reused_rank16_source,mimo_judge,mimo,strict_common_natural_k16,mimo_to_mimo,11241,11241,11240,1,0.999911,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k2,mimo_to_mimo,11241,11241,11238,3,0.999733,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k4,mimo_to_mimo,11241,11241,11233,8,0.999288,0,0,0,0,0,0,0,PASS
+global_leaderboard_pool_size_cost_efficiency,pool_size_primary,mimo_judge,mimo,strict_common_natural_k6,mimo_to_mimo,11241,11241,11237,4,0.999644,0,0,0,0,0,0,0,PASS

data/external/evidence/formal/five_benchmark_cost_efficiency/repair_audit_summary.md

@@ -0,0 +1,68 @@
+# Pool-Size 2x2 Repair Audit
+
+Status: PASS
+
+Date: 2026-07-02
+
+## Repair Targets
+
+| Population | Cell | Parse-ok after repair | Failed rows remaining | Status |
+| --- | --- | ---: | ---: | --- |
+| `strict_common_natural_k14` | `mimo_to_mimo` | 11,219 / 11,241 = 99.8043% | 22 | PASS |
+| `balanced_k4_1c3w` | `deepseek_to_mimo` | 2,135 / 2,136 = 99.9532% | 1 | PASS |
+| `balanced_k12_9c3w` | `mimo_to_mimo` | 23 / 23 = 100.0000% | 0 | PASS |
+
+All repair targets exceed the 98% parse-ok threshold.
+
+## Raw-Log Reconciliation
+
+Subagent validation found 23 successful final `task_log.jsonl` records in
+`strict_common_natural_k12 / deepseek_to_deepseek` that had not been absorbed into
+`details.csv`, `summary.csv`, and `resume_state.json`. These were existing
+successful ranking records, not new model calls.
+
+The cell was reconciled offline from its append-only raw log:
+
+- Before reconciliation: 11,217 / 11,241 parse-ok, 24 failed.
+- After reconciliation: 11,240 / 11,241 parse-ok, 1 failed.
+
+The top-level pool-size summaries were rebuilt offline after reconciliation.
+
+## Global Validity Checks
+
+- Total ranking tasks: 309,612
+- Total parse-ok rows: 308,456
+- Total failed rows: 1,156
+- Overall parse-ok rate: 99.6266%
+- Failed rows with non-empty ranking: 0
+- Bad JSONL lines: 0
+- Duplicate task/detail keys: 0
+- Denominator mismatches: 0
+- Parse-ok ranking permutation issues: 0
+- Raw successful final log records missing from final details: 0
+
+## Rebuilt Target Summaries
+
+- `strict_common_natural_k14 / mimo_to_mimo / rank@14`: `n_questions=11219`, accuracy `0.500758`, 95% CI `[0.491929, 0.509669]`.
+- `balanced_k4_1c3w / deepseek_to_mimo`: `n_pools=2135`, mean AUC `0.599063`, top1 correct rate `0.428103`.
+- `balanced_k12_9c3w / mimo_to_mimo`: `n_pools=23`, mean AUC `0.858293`, top1 correct rate `0.869565`.
+- Reconciled non-target check, `strict_common_natural_k12 / deepseek_to_deepseek / rank@12`: `n_questions=11240`, accuracy `0.643416`, 95% CI `[0.637353, 0.650538]`.
+
+## Validation Commands
+
+```bash
+.venv/bin/python scripts/run_experiment.py --config configs/experiments/pilot/cost_efficiency_pool_size_2x2_repair.yaml --dry-run
+ALLOW_EXTERNAL_MODEL_TRANSFER=1 OPENAI_BASE_URL=http://127.0.0.1:4002/v1 OPENAI_API_KEY=dummy .venv/bin/python scripts/run_experiment.py --config configs/experiments/pilot/cost_efficiency_pool_size_2x2_repair.yaml --require-llm
+.venv/bin/python scripts/run_experiment.py --config configs/experiments/pilot/cost_efficiency_pool_size_2x2_repair.yaml
+.venv/bin/python -m unittest tests.test_cost_efficiency_16sample -v
+.venv/bin/python -m unittest discover -s tests -p "test_*.py" -v
+```
+
+The offline rebuild required unsandboxed access to the local Hugging Face dataset cache lock, but did not use `--require-llm` and did not call an LLM endpoint. The raw-log reconciliation also did not call an LLM endpoint.
+
+## Remaining Caveats
+
+- This is still pilot evidence until author-approved formal promotion.
+- `balanced_k12_9c3w / mimo_to_mimo` remains a sparse ceiling stress-test cell even though parse-ok is now 100%.
+- Natural pool-size results are strict-common, parse-ok-filtered evidence.
+- Failed rows remain in the raw logs for auditability, but they do not enter accuracy or AUC summaries.

data/external/evidence/formal/five_benchmark_cost_efficiency/source_README.md

@@ -0,0 +1,7 @@
+# Source README
+
+This directory is a compact manuscript-facing mirror of `results/formal/five_benchmark_cost_efficiency/`.
+
+It intentionally keeps only summary tables and audits needed for writing and figure generation. Full selector tasks, details, raw logs, resume states, generated pool summaries, and the complete formal snapshot manifest remain in the formal results package.
+
+Use these files for the pool-size sensitivity and cost-efficiency claim. Do not treat balanced sparse ceiling cells as headline evidence.

data/external/evidence/formal/five_benchmark_cost_efficiency/source_paths.md

@@ -0,0 +1,7 @@
+# Source Paths
+
+- Formal package: `/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_cost_efficiency`
+- Source pilot: `/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/request_cost_estimation/global_replay_cost_efficiency_pool_size_2x2_pilot`
+- Reused rank-16 source: `/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/request_cost_estimation/global_replay_cost_efficiency_16sample_2x2_pilot`
+- Full selector rankings and raw logs remain in the formal package under `selector_rankings/`.
+- This manuscript evidence mirror contains compact tables for writing and figure generation.

data/external/evidence/formal/five_benchmark_selector_boundary/README.md

@@ -0,0 +1,19 @@
+# Five-Benchmark Selector Boundary
+
+## Writing Role
+Supports the main availability-reliability boundary claim by preserving the compact migration and completion manifests for the five-benchmark formal package.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md`
+- `manifest.csv`
+- `migration_selection.csv`
+- `boundary_completion_manifest.csv`
+
+## Full Source Package
+- `results/formal/five_benchmark_selector_boundary/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/five_benchmark_selector_boundary/boundary_completion_manifest.csv

@@ -0,0 +1,33 @@
+judge,judge_model_id,generator,benchmark,regime,input_pool_path,input_ranking_path,output_ranking_path,output_summary_path,tasks,parse_ok,parse_failed,status
+deepseek,deepseek_v4_flash_judge,deepseek,gpqa,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/gpqa/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking_summary.csv,0,0,0,skipped_no_tasks
+deepseek,deepseek_v4_flash_judge,deepseek,gpqa,balanced,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/gpqa/balanced_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/balanced_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/balanced_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/balanced_ranking_summary.csv,0,0,0,skipped_no_tasks
+deepseek,deepseek_v4_flash_judge,deepseek,medxpertqa,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/medxpertqa/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking_summary.csv,0,0,0,skipped_no_tasks
+deepseek,deepseek_v4_flash_judge,deepseek,medxpertqa,balanced,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/medxpertqa/balanced_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/balanced_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/balanced_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/balanced_ranking_summary.csv,0,0,0,skipped_no_tasks
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data/external/evidence/formal/five_benchmark_selector_boundary/source_README.md

@@ -0,0 +1,122 @@
+# Five-Benchmark Selector Boundary Formal Snapshot
+
+This directory is a filtered formal snapshot copied from:
+
+`/Users/jay/research/evole-meme/meme_evo_mas_pilot/results/five_benchmark_selector_boundary`
+
+It preserves the core selector-boundary evidence for the generator/judge matrix
+over `gpqa`, `medxpertqa`, `mmlu_pro`, and `musr`. A post-migration
+`hle_text_mc` extension has since been added after local validation. This is not
+a full copy of the legacy workspace. Balanced cross-model rankings that only
+existed in legacy aggregate files have been split into per-benchmark files in
+this snapshot.
+
+## Included Files
+
+- `generated_pools/deepseek_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `generated_pools/mimo_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `selector_rankings/deepseek_judge/deepseek_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `selector_rankings/deepseek_judge/mimo_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `selector_rankings/mimo_judge/deepseek_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `selector_rankings/mimo_judge/mimo_generated/{gpqa,medxpertqa,mmlu_pro,musr}/`
+- `generated_pools/{deepseek_generated,mimo_generated}/hle_text_mc/`
+- `selector_rankings/{deepseek_judge,mimo_judge}/{deepseek_generated,mimo_generated}/hle_text_mc/`
+
+The root `manifest.csv` and `migration_log.csv` are copied from the legacy
+workspace for provenance. `migration_selection.csv` is generated for this formal
+snapshot and records the exact copied and derived legacy file set. The
+post-migration `hle_text_mc` extension is not part of that migration index.
+
+## Excluded Files
+
+The migration intentionally excludes `bbh`, all `omni_math*` paths, `_aggregate`
+tables, logs, `.DS_Store`, provisional or superseded artifacts, debug batches,
+header-only files, and empty placeholders.
+
+Old Omni-MATH artifacts are excluded because that benchmark is being replaced by
+MATH-500 in the current formal workflow.
+
+## Provenance And Validation
+
+Use `migration_selection.csv` as the authoritative index for this snapshot. It
+records relative path, source path, target path, generator, judge, benchmark,
+stage, source size, source SHA-256, target SHA-256, and whether the copied file
+was covered by the legacy manifest. Rows with `source_kind=derived_from_aggregate`
+were split from legacy aggregate ranking files; their source SHA-256 identifies
+the aggregate source and their target SHA-256 identifies the derived file.
+
+There are 110 indexed files in this snapshot:
+
+- 49 generated-pool files
+- 58 selector-ranking files
+- 3 root provenance files
+
+The 18 Mimo-related selector-ranking files that were present on disk but missing
+from the legacy manifest are included and marked with `manifest_covered=false`.
+
+The balanced 2x2 matrix is represented per benchmark for all non-Omni cells.
+Twenty-one balanced files were derived during migration: 10 ranking files split
+from legacy aggregate files and 11 per-benchmark summaries.
+
+## HLE Text Multiple-Choice Extension
+
+The `hle_text_mc` sample banks and pools were generated in the pilot area,
+validated, and then copied into this formal path. The HLE selector rankings were
+run with the same judge cells and model specs as the other boundary-completion
+benchmarks, with HLE-specific `concurrency: 200` configs:
+
+- `configs/experiments/boundary_completion/test/hle_text_mc_selector_boundary_completion_test.yaml`
+- `configs/experiments/boundary_completion/test/hle_text_mc_selector_boundary_retry_failed_test.yaml`
+
+The HLE run manifests are copied as
+`hle_text_mc_boundary_completion_manifest.csv` and
+`hle_text_mc_boundary_retry_failed_manifest.csv`. After retries, dry-run
+validation reported zero remaining HLE retry tasks.
+
+Current HLE selector-ranking status:
+
+- selector-ranking files: 8
+- total ranking rows: 9868
+- parse-ok rows: 9868
+- parse-failed rows retained as empty rankings: 0
+
+## Boundary Completion Run
+
+Missing selector rankings were completed with:
+
+`configs/experiments/boundary_completion/formal/five_benchmark_selector_boundary_completion.yaml`
+
+The completion runner uses a global task queue across active cells, benchmarks,
+and regimes with total `concurrency: 400`. The formal run only fills missing
+pool rankings; rows that still fail strict ranking parsing are preserved for a
+later retry/audit pass rather than repeatedly retried in the missing-fill pass.
+
+Parse-failed rows were retried with:
+
+`configs/experiments/boundary_completion/formal/five_benchmark_selector_boundary_retry_failed.yaml`
+
+The retry pass uses the same global `concurrency: 400` runner with
+`fill_missing: false` and `retry_parse_failures: true`, so it only revisits rows
+whose previous outputs failed parsing.
+
+The GPQA question source is loaded from the public GPQA dataset zip fallback and
+normalized as `gpqa_extended`, matching the migrated pool identifiers. LLM calls
+use the configured model endpoint without setting `max_tokens`.
+
+Current formal CSV status after the retry-failed pass, including the HLE
+extension:
+
+- selector-ranking files: 40
+- total ranking rows: 313438
+- parse-ok rows: 313434
+- parse-failed rows retained as empty rankings: 4
+
+Remaining failures are from the original non-HLE boundary-completion run and are
+strict-parser failures, not missing rows or API timeouts. All four retained rows
+are `mimo` judge outputs on `mmlu_pro` whose responses were not valid full
+permutations of the eight prompt candidate IDs: `1619_balanced_2c6w`,
+`1212_natural_8_r2`, `199_natural_8_r2`, and `1867_natural_8_r0`.
+
+Run status is indexed in `boundary_completion_manifest.csv` and
+`boundary_retry_failed_manifest.csv`; logs are written under
+`logs/boundary_completion/`.

data/external/evidence/formal/five_benchmark_selector_boundary/source_paths.md

@@ -0,0 +1,19 @@
+# Five-Benchmark Selector Boundary
+
+## Writing Role
+Path map for the compact five-benchmark selector-boundary mirror used in manuscript writing and review.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md` from `results/formal/five_benchmark_selector_boundary/README.md`
+- `manifest.csv` from `results/formal/five_benchmark_selector_boundary/manifest.csv`
+- `migration_selection.csv` from `results/formal/five_benchmark_selector_boundary/migration_selection.csv`
+- `boundary_completion_manifest.csv` from `results/formal/five_benchmark_selector_boundary/boundary_completion_manifest.csv`
+
+## Full Source Package
+- `results/formal/five_benchmark_selector_boundary/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/global_leaderboard_replay/README.md

@@ -0,0 +1,23 @@
+# Global Leaderboard Replay
+
+## Writing Role
+Supports the global natural-pool replay claim by mirroring compact coverage, benchmark, paired-delta, stratified, and ranking-completion summaries.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md`
+- `coverage_audit.csv`
+- `benchmark_summary.csv`
+- `paired_deltas.csv`
+- `stratified_summary.csv`
+- `formal_snapshot_manifest.csv`
+- `ranking_completion_manifest.csv`
+
+## Full Source Package
+- `results/formal/global_leaderboard_diffusion/`
+- `results/formal/global_leaderboard_ranking_completion/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/global_leaderboard_replay/benchmark_summary.csv

@@ -0,0 +1,31 @@
+experiment_id,benchmark,strategy,n_questions,accuracy,ci_low,ci_high
+global_leaderboard_diffusion_pilot,__global__,direct_single_random,16278,0.425284,0.421336,0.429219
+global_leaderboard_diffusion_pilot,__global__,majority_vote,16278,0.638191,0.632391,0.643948
+global_leaderboard_diffusion_pilot,__global__,rank_soft_copy,16278,0.690355,0.684875,0.695933
+global_leaderboard_diffusion_pilot,__global__,rank_top1_copy,16278,0.690355,0.684875,0.695933
+global_leaderboard_diffusion_pilot,__global__,shuffled_rank_soft_copy,16278,0.424694,0.420755,0.428794
+global_leaderboard_diffusion_pilot,gpqa,direct_single_random,546,0.550623,0.528370,0.573120
+global_leaderboard_diffusion_pilot,gpqa,majority_vote,546,0.713143,0.684556,0.743673
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data/external/evidence/formal/global_leaderboard_replay/coverage_audit.csv

@@ -0,0 +1,6 @@
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data/external/evidence/formal/global_leaderboard_replay/formal_snapshot_manifest.csv

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data/external/evidence/formal/global_leaderboard_replay/paired_deltas.csv

@@ -0,0 +1,137 @@
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+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_0_0p125,rank_top1_copy_minus_rank_soft_copy,1195,0.000000,0.000000,0.000000
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+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_0p125_0p625,rank_soft_copy_minus_majority_vote,7709,0.067336,0.061208,0.073527
+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_0p125_0p625,rank_soft_copy_minus_shuffled_rank_soft_copy,7709,0.393223,0.387644,0.398933
+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_0p125_0p625,rank_top1_copy_minus_rank_soft_copy,7709,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_0p625_1,rank_soft_copy_minus_direct_single_random,2831,0.168393,0.163083,0.173551
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+global_leaderboard_diffusion_pilot,mmlu_pro,p_correct_eq_1,rank_top1_copy_minus_rank_soft_copy,284,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,__all__,rank_soft_copy_minus_direct_single_random,756,0.194034,0.170079,0.216297
+global_leaderboard_diffusion_pilot,musr,__all__,rank_soft_copy_minus_majority_vote,756,0.106148,0.081597,0.129528
+global_leaderboard_diffusion_pilot,musr,__all__,rank_soft_copy_minus_shuffled_rank_soft_copy,756,0.195376,0.171268,0.217149
+global_leaderboard_diffusion_pilot,musr,__all__,rank_top1_copy_minus_rank_soft_copy,756,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_0_0p125,rank_soft_copy_minus_direct_single_random,4,-0.082500,-0.095000,-0.067500
+global_leaderboard_diffusion_pilot,musr,p_correct_0_0p125,rank_soft_copy_minus_majority_vote,4,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_0_0p125,rank_soft_copy_minus_shuffled_rank_soft_copy,4,-0.097500,-0.134000,-0.075500
+global_leaderboard_diffusion_pilot,musr,p_correct_0_0p125,rank_top1_copy_minus_rank_soft_copy,4,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_0p125_0p625,rank_soft_copy_minus_direct_single_random,641,0.197488,0.168830,0.225325
+global_leaderboard_diffusion_pilot,musr,p_correct_0p125_0p625,rank_soft_copy_minus_majority_vote,641,0.129376,0.099507,0.159357
+global_leaderboard_diffusion_pilot,musr,p_correct_0p125_0p625,rank_soft_copy_minus_shuffled_rank_soft_copy,641,0.200016,0.171447,0.226671
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+global_leaderboard_diffusion_pilot,musr,p_correct_0p625_1,rank_soft_copy_minus_direct_single_random,105,0.194571,0.170181,0.218571
+global_leaderboard_diffusion_pilot,musr,p_correct_0p625_1,rank_soft_copy_minus_majority_vote,105,-0.025543,-0.045192,-0.007596
+global_leaderboard_diffusion_pilot,musr,p_correct_0p625_1,rank_soft_copy_minus_shuffled_rank_soft_copy,105,0.189371,0.166321,0.213184
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+global_leaderboard_diffusion_pilot,musr,p_correct_eq_0,rank_soft_copy_minus_direct_single_random,1,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_eq_0,rank_soft_copy_minus_majority_vote,1,0.000000,0.000000,0.000000
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+global_leaderboard_diffusion_pilot,musr,p_correct_eq_1,rank_soft_copy_minus_majority_vote,5,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_eq_1,rank_soft_copy_minus_shuffled_rank_soft_copy,5,0.000000,0.000000,0.000000
+global_leaderboard_diffusion_pilot,musr,p_correct_eq_1,rank_top1_copy_minus_rank_soft_copy,5,0.000000,0.000000,0.000000

data/external/evidence/formal/global_leaderboard_replay/ranking_completion_manifest.csv

@@ -0,0 +1,6 @@
+judge,judge_model_id,generator,benchmark,regime,input_pool_path,input_ranking_path,output_ranking_path,output_summary_path,tasks,parse_ok,parse_failed,status
+deepseek,deepseek_v4_flash_official_judge,deepseek,mmlu_pro,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/mmlu_pro/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/mmlu_pro/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/mmlu_pro/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/mmlu_pro/natural_ranking_summary.csv,3951,3951,0,completed
+deepseek,deepseek_v4_flash_official_judge,deepseek,gpqa,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/gpqa/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/gpqa/natural_ranking_summary.csv,61,61,0,completed
+deepseek,deepseek_v4_flash_official_judge,deepseek,medxpertqa,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/medxpertqa/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/medxpertqa/natural_ranking_summary.csv,3099,3099,0,completed
+deepseek,deepseek_v4_flash_official_judge,deepseek,musr,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/musr/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/musr/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/musr/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/musr/natural_ranking_summary.csv,31,31,0,completed
+deepseek,deepseek_v4_flash_official_judge,deepseek,hle_text_mc,natural,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/generated_pools/deepseek_generated/hle_text_mc/natural_pools.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/formal/five_benchmark_selector_boundary/selector_rankings/deepseek_judge/deepseek_generated/hle_text_mc/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/hle_text_mc/natural_ranking.csv,/Users/jay/research/evole-meme/reasoning-meme-mechanism/results/pilots/global_leaderboard_ranking_completion/selector_rankings/deepseek_judge/deepseek_generated/hle_text_mc/natural_ranking_summary.csv,563,563,0,completed

data/external/evidence/formal/global_leaderboard_replay/source_README.md

@@ -0,0 +1,96 @@
+# Complete Natural-Pool Replay Formal Snapshot
+
+This directory formalizes the completed frozen natural-pool replay promoted
+from `results/pilots/global_leaderboard_diffusion` after local consistency
+checks and read-only subagent validation.
+
+The replay tests whether selector-guided transmission improves final task
+accuracy over direct single-sample answering, majority voting, shuffled
+ranking, and top-1 copying on the complete natural-pool benchmark set from
+`results/formal/five_benchmark_selector_boundary`.
+
+## Scope
+
+- Benchmarks: MMLU-Pro, GPQA, MedXpertQA, MuSR, HLE multiple-choice
+- Generator: DeepSeek
+- Ranking judge: DeepSeek
+- Natural pools: 81,390
+- Questions: 16,278
+- Strategies: `direct_single_random`, `majority_vote`,
+  `shuffled_rank_soft_copy`, `rank_soft_copy`, `rank_top1_copy`
+- Bootstrap resamples: 1000
+- Bootstrap seed: 20260628
+
+## Included Files
+
+- `coverage_audit.csv`
+  - Per-benchmark coverage audit. All five rows are `status=ok`, with zero
+    missing ranked pools and zero invalid rankings.
+- `coverage_missing_pools.csv`
+  - Header-only missing-pool audit table.
+- `benchmark_summary.csv`
+  - Per-benchmark and global accuracy with bootstrap intervals.
+- `paired_deltas.csv`
+  - Paired strategy contrasts with bootstrap intervals.
+- `stratified_summary.csv`
+  - Accuracy summaries stratified by observed correct-candidate prevalence.
+- `question_scores.csv`
+  - Question-level strategy scores used to derive the summary and paired
+    contrast tables.
+- `formal_snapshot_manifest.csv`
+  - Promotion manifest with source paths, target paths, byte sizes, and
+    SHA-256 hashes.
+
+Each promoted CSV has a sibling `.metadata.json` sidecar generated during
+formal promotion.
+
+## Explicitly Excluded
+
+- `replay_details.csv`
+  - The raw replay trace table is intentionally not promoted because it is a
+    2.6 GB intermediate artifact. It remains in the pilot directory for local
+    trace-level inspection.
+- `replay_details.metadata.json`
+  - Excluded with the raw replay trace table.
+
+## Main Readout
+
+Global question accuracy:
+
+| strategy | accuracy |
+| --- | ---: |
+| direct single random | 42.53% |
+| shuffled rank-soft copying | 42.47% |
+| majority voting | 63.82% |
+| rank-guided copying | 69.04% |
+| top-1 copying | 69.04% |
+
+Headline paired effects for rank-guided copying:
+
+| contrast | mean delta | 95% CI |
+| --- | ---: | --- |
+| vs direct single random | +26.51 pp | [+26.09, +26.91] |
+| vs shuffled rank-soft copying | +26.57 pp | [+26.15, +26.97] |
+| vs majority voting | +5.22 pp | [+4.85, +5.59] |
+
+The formal interpretation remains bounded. Rank-guided copying improves the
+overall frozen-pool accuracy and beats majority voting globally, but it does
+not universally dominate majority voting. In the high-availability stratum
+`0.625 < p_correct < 1`, rank-guided copying underperforms majority voting by
+3.22 percentage points, 95% CI [-3.62, -2.82].
+
+## Validation
+
+The promoted pilot passed the following checks before formalization:
+
+- `coverage_audit.csv` has all intended benchmarks and all `status=ok`.
+- `coverage_missing_pools.csv` is header-only.
+- Total covered questions are 16,278.
+- Total natural pools are 81,390.
+- `question_scores.csv` has 81,390 rows, exactly 16,278 questions times 5
+  strategies.
+- `benchmark_summary.csv`, `stratified_summary.csv`, and `paired_deltas.csv`
+  were independently recomputed from `question_scores.csv` by a read-only
+  subagent with zero mismatches.
+- The ranking overlay support package is formalized separately under
+  `results/formal/global_leaderboard_ranking_completion`.

data/external/evidence/formal/global_leaderboard_replay/source_paths.md

@@ -0,0 +1,23 @@
+# Global Leaderboard Replay
+
+## Writing Role
+Path map for the compact global leaderboard replay mirror used in manuscript writing and source review.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md` from `results/formal/global_leaderboard_diffusion/README.md`
+- `coverage_audit.csv` from `results/formal/global_leaderboard_diffusion/coverage_audit.csv`
+- `benchmark_summary.csv` from `results/formal/global_leaderboard_diffusion/benchmark_summary.csv`
+- `paired_deltas.csv` from `results/formal/global_leaderboard_diffusion/paired_deltas.csv`
+- `stratified_summary.csv` from `results/formal/global_leaderboard_diffusion/stratified_summary.csv`
+- `formal_snapshot_manifest.csv` from `results/formal/global_leaderboard_diffusion/formal_snapshot_manifest.csv`
+- `ranking_completion_manifest.csv` from `results/formal/global_leaderboard_ranking_completion/boundary_completion_manifest.csv`
+
+## Full Source Package
+- `results/formal/global_leaderboard_diffusion/`
+- `results/formal/global_leaderboard_ranking_completion/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/global_leaderboard_replay/stratified_summary.csv

@@ -0,0 +1,141 @@
+experiment_id,benchmark,stratum,strategy,n_questions,accuracy,ci_low,ci_high
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+global_leaderboard_diffusion_pilot,__global__,p_correct_0_0p125,rank_top1_copy,2407,0.128292,0.120895,0.136022
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+global_leaderboard_diffusion_pilot,__global__,p_correct_eq_1,direct_single_random,332,1.000000,1.000000,1.000000
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+global_leaderboard_diffusion_pilot,gpqa,p_correct_0_0p125,direct_single_random,7,0.090000,0.060000,0.117214
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+global_leaderboard_diffusion_pilot,gpqa,p_correct_0_0p125,shuffled_rank_soft_copy,7,0.060857,0.029714,0.097157
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p125_0p625,direct_single_random,347,0.396340,0.381643,0.411821
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p125_0p625,majority_vote,347,0.569890,0.535029,0.601991
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p125_0p625,rank_soft_copy,347,0.673775,0.633991,0.711816
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p125_0p625,rank_top1_copy,347,0.673775,0.633991,0.711816
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p125_0p625,shuffled_rank_soft_copy,347,0.397573,0.381837,0.413263
+global_leaderboard_diffusion_pilot,gpqa,p_correct_0p625_1,direct_single_random,154,0.808312,0.792011,0.824351
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data/external/evidence/formal/prospective_diffusion_minority/README.md

@@ -0,0 +1,23 @@
+# Prospective Diffusion Minority
+
+## Writing Role
+Supports the minority rank-guided diffusion result and its GPQA/MiMo low-availability diagnostic with compact bootstrap and diagnostic summaries.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md`
+- `diffusion_strategy_bootstrap_ci.csv`
+- `selector_delta_bootstrap_ci.csv`
+- `metadata.json`
+- `diagnostic/cell_diagnostic_summary.csv`
+- `diagnostic/gpqa_mimo_low_availability_deepseek_split.csv`
+- `diagnostic/gpqa_mimo_low_availability_pool_diagnostic.csv`
+
+## Full Source Package
+- `results/formal/prospective_diffusion_minority_evidence/`
+- `results/formal/prospective_diffusion_minority_diagnostic/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/prospective_diffusion_minority/diagnostic/cell_diagnostic_summary.csv

@@ -0,0 +1,10 @@
+benchmark,generator,judge,stratum,n_pools,mean_pool_p_correct,max_pool_p_correct,mean_question_p_correct,rank_soft_delta,ssop_delta,shuffled_delta,natural_delta,live_top1_correct_rate,live_top2_correct_rate,deepseek_same_question_p_mean,deepseek_same_question_p_median,deepseek_same_question_p_ge_0_5_rate,deepseek_same_question_sample0_correct_rate
+gpqa,deepseek,deepseek,boundary,80,0.165625,0.375,0.29296875,0.1855208738,-0.05733366016,0.009451081319,0,0.525,0.575,0.29296875,0.3125,0,0.3375
+gpqa,deepseek,deepseek,high_potential,80,0.3203125,0.375,0.50625,0.3444778312,0.3643627514,0.001033168223,0,0.7375,0.8,0.50625,0.5,0.7875,0.6125
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+hle_text_mc,deepseek,deepseek,boundary,80,0.1484375,0.375,0.2217199901,0.01997155043,-0.09113776117,0.01336279461,0,0.2,0.3,,,,
+hle_text_mc,deepseek,deepseek,high_potential,80,0.234375,0.375,0.3818199283,0.1579689119,0.1339540122,-0.04387363216,0,0.4625,0.5375,,,,
+hle_text_mc,deepseek,deepseek,low_availability,80,0.13125,0.25,0.07678251653,-0.04442360303,-0.1312464552,0.001753917376,0,0.0875,0.175,,,,

data/external/evidence/formal/prospective_diffusion_minority/diagnostic/gpqa_mimo_low_availability_deepseek_split.csv

@@ -0,0 +1,3 @@
+group,n_pools,mean_rank_soft_delta,median_rank_soft_delta,positive_delta_rate,majority_true_rate,live_top1_correct_rate,live_top2_correct_rate,deepseek_sample0_correct_rate,mean_deepseek_p_correct_same_question,median_deepseek_p_correct_same_question
+deepseek_p_lt_0_5,42,0.05464789839,-0.09141899766,0.380952381,0.2857142857,0.2857142857,0.3333333333,0.3333333333,0.2927827381,0.25
+deepseek_p_ge_0_5,38,0.2882042421,0.4054325304,0.8157894737,0.6842105263,0.6842105263,0.7631578947,0.7368421053,0.7384868421,0.75

data/external/evidence/formal/prospective_diffusion_minority/diagnostic/gpqa_mimo_low_availability_pool_diagnostic.csv

@@ -0,0 +1,81 @@
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+gpqa,mimo,deepseek,low_availability,gpqa_recQiVCk4JA9236Nw,gpqa_recQiVCk4JA9236Nw_natural_8_r0,0.25,0.25,0.552496115,1,1,1,16,10,0.625,1,deepseek_p_ge_0_5
+gpqa,mimo,deepseek,low_availability,gpqa_recTq9xGFD0HRvC7n,gpqa_recTq9xGFD0HRvC7n_natural_8_r1,0.25,0.25,0.552496115,1,1,1,16,6,0.375,0,deepseek_p_lt_0_5
+gpqa,mimo,deepseek,low_availability,gpqa_recVEXvhYxAhELVqB,gpqa_recVEXvhYxAhELVqB_natural_8_r0,0.25,0.25,0.552496115,1,1,1,16,16,1,1,deepseek_p_ge_0_5
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data/external/evidence/formal/prospective_diffusion_minority/diffusion_strategy_bootstrap_ci.csv

@@ -0,0 +1,37 @@
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+gpqa,mimo,deepseek,natural,boundary,natural_copy,Natural copy,73,0.25,0.1575342466,0.25,0.8592857056,0.06736606981,0.1575342466,0.1575342466,0,0,0,0,0,0,0,0,0
+gpqa,mimo,deepseek,natural,boundary,rank_soft_copy,Rank-soft,73,0.25,0.1575342466,0.25,0.8592857056,0.06736606981,0.1575342466,0.4084930797,0.2509588331,0.1926988592,0.3079764596,0.602739726,0.4931506849,0.7123287671,1.952752473,1.477838667,2.398117623
+gpqa,mimo,deepseek,natural,boundary,shuffled_rank_soft_copy,Shuffled rank-soft,73,0.25,0.1575342466,0.25,0.8592857056,0.06736606981,0.1575342466,0.1315129252,-0.0260213214,-0.06157399647,0.01112592933,0.09589041096,0.04109589041,0.1643835616,-0.2319925973,-0.5026156281,0.05786499147
+gpqa,mimo,deepseek,natural,boundary,ssop_answer_cluster_sparse_refine,SSOP,73,0.25,0.1575342466,0.25,0.8592857056,0.06736606981,0.1575342466,0.1298924651,-0.02764178149,-0.08484604315,0.03711723605,0.1232876712,0.05479452055,0.2054794521,-0.4996721938,-0.8402184782,-0.1165343152
+gpqa,mimo,deepseek,natural,high_potential,natural_copy,Natural copy,80,0.2578125,0.1671875,0.375,0.8627379497,0.06921105048,0.1671875,0.1671875,0,0,0,0,0,0,0,0,0
+gpqa,mimo,deepseek,natural,high_potential,rank_soft_copy,Rank-soft,80,0.2578125,0.1671875,0.375,0.8627379497,0.06921105048,0.1671875,0.396810857,0.229623357,0.1696193354,0.2906339284,0.575,0.4625,0.6875,1.735828986,1.282444411,2.163161962
+gpqa,mimo,deepseek,natural,high_potential,shuffled_rank_soft_copy,Shuffled rank-soft,80,0.2578125,0.1671875,0.375,0.8627379497,0.06921105048,0.1671875,0.1587321533,-0.008455346744,-0.05085400277,0.037310429,0.1625,0.0875,0.25,-0.03448011861,-0.3666500452,0.3200145226
+gpqa,mimo,deepseek,natural,high_potential,ssop_answer_cluster_sparse_refine,SSOP,80,0.2578125,0.1671875,0.375,0.8627379497,0.06921105048,0.1671875,0.1751645315,0.00797703147,-0.05917956555,0.08140059081,0.1625,0.0875,0.25,-0.2872176428,-0.6642435289,0.131876349
+gpqa,mimo,deepseek,natural,low_availability,natural_copy,Natural copy,80,0.24921875,0.1546875,0.25,0.8584144791,0.06707545467,0.1546875,0.1546875,0,0,0,0,0,0,0,0,0
+gpqa,mimo,deepseek,natural,low_availability,rank_soft_copy,Rank-soft,80,0.24921875,0.1546875,0.25,0.8584144791,0.06707545467,0.1546875,0.3202746617,0.1655871617,0.1053863353,0.2253097431,0.475,0.3625,0.5875,1.259581468,0.7624894666,1.73510217
+gpqa,mimo,deepseek,natural,low_availability,shuffled_rank_soft_copy,Shuffled rank-soft,80,0.24921875,0.1546875,0.25,0.8584144791,0.06707545467,0.1546875,0.146893818,-0.007793682014,-0.04619791667,0.03264121585,0.1375,0.0625,0.2125,-0.04006780251,-0.351055823,0.2978990686
+gpqa,mimo,deepseek,natural,low_availability,ssop_answer_cluster_sparse_refine,SSOP,80,0.24921875,0.1546875,0.25,0.8584144791,0.06707545467,0.1546875,0.1188915752,-0.03579592482,-0.09451043995,0.03169322616,0.125,0.0625,0.2,-0.5540065649,-0.8949746628,-0.1860232066
+hle_text_mc,deepseek,deepseek,natural,boundary,natural_copy,Natural copy,80,0.2217199901,0.1484375,0.375,0.5600484859,0.01056765362,0.1484375,0.1484375,0,0,0,0,0,0,0,0,0
+hle_text_mc,deepseek,deepseek,natural,boundary,rank_soft_copy,Rank-soft,80,0.2217199901,0.1484375,0.375,0.5600484859,0.01056765362,0.1484375,0.1684090504,0.01997155043,-0.02870505436,0.07086864741,0.2,0.1125,0.2875,0.1598204265,-0.2103623498,0.5664416526
+hle_text_mc,deepseek,deepseek,natural,boundary,shuffled_rank_soft_copy,Shuffled rank-soft,80,0.2217199901,0.1484375,0.375,0.5600484859,0.01056765362,0.1484375,0.1618002946,0.01336279461,-0.03088163284,0.05923813454,0.175,0.1,0.2625,0.186985792,-0.1768525841,0.5847286194
+hle_text_mc,deepseek,deepseek,natural,boundary,ssop_answer_cluster_sparse_refine,SSOP,80,0.2217199901,0.1484375,0.375,0.5600484859,0.01056765362,0.1484375,0.05729973882,-0.09113776117,-0.1311795558,-0.04266229582,0.0625,0.0125,0.125,-0.8882217073,-1.104303321,-0.6184860839
+hle_text_mc,deepseek,deepseek,natural,high_potential,natural_copy,Natural copy,80,0.3818199283,0.234375,0.375,0.7075332799,0.04752519071,0.234375,0.234375,0,0,0,0,0,0,0,0,0
+hle_text_mc,deepseek,deepseek,natural,high_potential,rank_soft_copy,Rank-soft,80,0.3818199283,0.234375,0.375,0.7075332799,0.04752519071,0.234375,0.3923439119,0.1579689119,0.08649016203,0.2285550365,0.4625,0.35,0.575,0.8615937767,0.4509968135,1.278053869
+hle_text_mc,deepseek,deepseek,natural,high_potential,shuffled_rank_soft_copy,Shuffled rank-soft,80,0.3818199283,0.234375,0.375,0.7075332799,0.04752519071,0.234375,0.1905013678,-0.04387363216,-0.08804365268,0.00294022456,0.175,0.1,0.2625,-0.2985428152,-0.545486209,-0.03286707344
+hle_text_mc,deepseek,deepseek,natural,high_potential,ssop_answer_cluster_sparse_refine,SSOP,80,0.3818199283,0.234375,0.375,0.7075332799,0.04752519071,0.234375,0.3683290122,0.1339540122,0.04244482369,0.2292851428,0.375,0.275,0.475,0.4689971864,-0.0176233699,0.9626866579
+hle_text_mc,deepseek,deepseek,natural,low_availability,natural_copy,Natural copy,80,0.07678251653,0.13125,0.25,0.501853319,0.0001641951833,0.13125,0.13125,0,0,0,0,0,0,0,0,0
+hle_text_mc,deepseek,deepseek,natural,low_availability,rank_soft_copy,Rank-soft,80,0.07678251653,0.13125,0.25,0.501853319,0.0001641951833,0.13125,0.08682639699,-0.04442360303,-0.07891838053,-0.006831809694,0.0875,0.025,0.15,-0.3647972398,-0.671417352,-0.02701468674
+hle_text_mc,deepseek,deepseek,natural,low_availability,shuffled_rank_soft_copy,Shuffled rank-soft,80,0.07678251653,0.13125,0.25,0.501853319,0.0001641951833,0.13125,0.1330039174,0.001753917376,-0.03402365502,0.04141265924,0.125,0.0625,0.2,0.006766535974,-0.3074934903,0.3580853483
+hle_text_mc,deepseek,deepseek,natural,low_availability,ssop_answer_cluster_sparse_refine,SSOP,80,0.07678251653,0.13125,0.25,0.501853319,0.0001641951833,0.13125,3.544837768e-06,-0.1312464552,-0.1374983319,-0.1265552159,0,0,0,-1.152348545,-1.161889494,-1.145175538

data/external/evidence/formal/prospective_diffusion_minority/metadata.json

@@ -0,0 +1,42 @@
+{
+  "bootstrap": {
+    "confidence_level": 0.95,
+    "paired_delta": "rank_soft_copy - shuffled_rank_soft_copy paired by pool_id",
+    "resamples": 5000,
+    "seed": 20260626,
+    "unit": "pool"
+  },
+  "generated_at_utc": "2026-06-25T16:18:01.849324+00:00",
+  "generated_from_git_commit": "1819f6316b46aa4f639935f6df6cb5ac5e2e1eeb",
+  "inputs": [
+    "results/pilots/prospective_diffusion_minority/live_replay/details.csv",
+    "results/pilots/prospective_diffusion_minority/live_replay/summary.csv",
+    "results/pilots/prospective_diffusion_minority/live_rerank/summary.csv",
+    "results/formal/prospective_diffusion_minority_diagnostic/cell_diagnostic_summary.csv",
+    "results/formal/prospective_diffusion_minority_diagnostic/gpqa_mimo_low_availability_deepseek_split.csv"
+  ],
+  "outputs": [
+    "results/formal/prospective_diffusion_minority_evidence/diffusion_strategy_bootstrap_ci.csv",
+    "results/formal/prospective_diffusion_minority_evidence/selector_delta_bootstrap_ci.csv",
+    "results/formal/prospective_diffusion_minority_evidence/README.md",
+    "manuscript/figures/staged_article/fig8_minority_diffusion_delta.png",
+    "manuscript/figures/staged_article/fig8_minority_diffusion_delta.pdf",
+    "manuscript/figures/staged_article/fig9_selector_signal_vs_diffusion.png",
+    "manuscript/figures/staged_article/fig9_selector_signal_vs_diffusion.pdf",
+    "manuscript/figures/staged_article/fig10_mimo_exception_diagnostic.png",
+    "manuscript/figures/staged_article/fig10_mimo_exception_diagnostic.pdf",
+    "manuscript/draft/paper_v1/prospective_diffusion_minority_evidence/results_section.md",
+    "manuscript/draft/paper_v1/prospective_diffusion_minority_evidence/source_manifest.md"
+  ],
+  "validation": {
+    "all_pool_p_correct_lt_0_5": true,
+    "details_rows": 2852,
+    "max_pool_p_correct": 0.375,
+    "rank_ci_positive_cells": 6,
+    "rank_positive_cells": 7,
+    "selector_rows": 9,
+    "shuffled_near_zero_cells_abs_lt_0_05": 9,
+    "ssop_mean_beats_rank_cells": 1,
+    "strategy_rows": 36
+  }
+}

data/external/evidence/formal/prospective_diffusion_minority/selector_delta_bootstrap_ci.csv

@@ -0,0 +1,10 @@
+benchmark,generator,judge,regime,stratum,n_pools,mean_question_p_correct,mean_pool_p_correct,max_pool_p_correct,rank_soft_mean_delta,rank_soft_ci_low,rank_soft_ci_high,shuffled_mean_delta,shuffled_ci_low,shuffled_ci_high,natural_mean_delta,natural_ci_low,natural_ci_high,ssop_mean_delta,ssop_ci_low,ssop_ci_high,rank_minus_shuffled_mean,rank_minus_shuffled_ci_low,rank_minus_shuffled_ci_high,ssop_minus_rank_mean,ssop_minus_rank_ci_low,ssop_minus_rank_ci_high
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+hle_text_mc,deepseek,deepseek,natural,low_availability,80,0.07678251653,0.13125,0.25,-0.04442360303,-0.07860808102,-0.00690958565,0.001753917376,-0.03445572006,0.03993260934,0,0,0,-0.1312464552,-0.13749812,-0.1265552076,-0.0461775204,-0.1007011926,0.00573714913,-0.08682285213,-0.1228264669,-0.05407291285

data/external/evidence/formal/prospective_diffusion_minority/source_README.md

@@ -0,0 +1,19 @@
+# Minority Diffusion Evidence Package
+
+This directory contains manuscript-facing derived evidence for the minority-correct prospective diffusion pilot. The raw live generation, live reranking, and replay artifacts remain under `results/pilots/prospective_diffusion_minority/`.
+
+## Scope
+
+The test condition is deliberately hard: every selected pool has a minority of correct answers (`pool_p_correct < 0.5`, maximum observed pool prevalence <= 0.375). This asks whether selector-driven transmission can rescue correct memes when the natural majority is wrong.
+
+## Generated outputs
+
+- `diffusion_strategy_bootstrap_ci.csv`: strategy-level means and deterministic 95% pool-bootstrap intervals for 36 benchmark/generator/stratum/strategy cells.
+- `selector_delta_bootstrap_ci.csv`: paired cell-level comparison of rank-soft, shuffled rank-soft, natural copy, and SSOP for 9 benchmark/generator/stratum cells.
+- `metadata.json`: source paths, bootstrap settings, and generation metadata.
+
+## Main readout
+
+Rank-soft is the stable main mechanism: 7/9 cells have positive mean diffusion gain, and 6/9 cells have a bootstrap interval entirely above zero. Shuffled rank-soft is close to zero in 9/9 cells, showing that the rank signal rather than diffusion mechanics alone drives the effect. SSOP beats rank-soft by mean paired delta in 1/9 cells, so it should be reported as conditional rather than the primary prospective mechanism.
+
+The strongest rank-soft cell is `GPQA / DeepSeek / high potential` with mean delta 0.3444778312. The weakest is `HLE MC / DeepSeek / low availability` with mean delta -0.04442360303.

data/external/evidence/formal/prospective_diffusion_minority/source_paths.md

@@ -0,0 +1,23 @@
+# Prospective Diffusion Minority
+
+## Writing Role
+Path map for the compact minority diffusion mirror and nested diagnostic artifacts.
+
+## Evidence Status
+formal
+
+## Mirrored Files
+- `source_README.md` from `results/formal/prospective_diffusion_minority_evidence/README.md`
+- `diffusion_strategy_bootstrap_ci.csv` from `results/formal/prospective_diffusion_minority_evidence/diffusion_strategy_bootstrap_ci.csv`
+- `selector_delta_bootstrap_ci.csv` from `results/formal/prospective_diffusion_minority_evidence/selector_delta_bootstrap_ci.csv`
+- `metadata.json` from `results/formal/prospective_diffusion_minority_evidence/metadata.json`
+- `diagnostic/cell_diagnostic_summary.csv` from `results/formal/prospective_diffusion_minority_diagnostic/cell_diagnostic_summary.csv`
+- `diagnostic/gpqa_mimo_low_availability_deepseek_split.csv` from `results/formal/prospective_diffusion_minority_diagnostic/gpqa_mimo_low_availability_deepseek_split.csv`
+- `diagnostic/gpqa_mimo_low_availability_pool_diagnostic.csv` from `results/formal/prospective_diffusion_minority_diagnostic/gpqa_mimo_low_availability_pool_diagnostic.csv`
+
+## Full Source Package
+- `results/formal/prospective_diffusion_minority_evidence/`
+- `results/formal/prospective_diffusion_minority_diagnostic/`
+
+## Copy Policy
+Large raw traces and complete answer/ranking banks remain in the source package.

data/external/evidence/formal/prospective_diffusion_perturbation/figures/paired_auc_deltas.metadata.json

@@ -0,0 +1,24 @@
+{
+  "artifact_kind": "analysis_auxiliary",
+  "command_mode": "prospective_rerank_perturbation_summary",
+  "config_hash": "b700db998f62",
+  "config_path": "configs/analyses/prospective_diffusion_perturbation_rerank_summary_formal.yaml",
+  "evidence_status": "complete",
+  "generated_at_utc": "2026-07-13T20:37:46.799784+00:00",
+  "git_commit": "cb0cf3a1edce4fa95964c58e2d0540c7462c2275",
+  "input_paths": [
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/rationale_only/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_only/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_plus_rationale/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/rationale_scrambled/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_scrambled/rankings.csv"
+  ],
+  "output_paths": [
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/summary.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/paired_contrasts.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/paired_auc_deltas.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_overall_top1_top2.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_by_stratum_top1.png"
+  ],
+  "run_class": "formal"
+}

data/external/evidence/formal/prospective_diffusion_perturbation/figures/paired_top1_deltas.metadata.json

@@ -0,0 +1,24 @@
+{
+  "artifact_kind": "analysis_auxiliary",
+  "command_mode": "prospective_rerank_perturbation_summary",
+  "config_hash": "b6097a9fc359",
+  "config_path": "configs/analyses/prospective_diffusion_perturbation_rerank_summary_formal.yaml",
+  "evidence_status": "complete",
+  "generated_at_utc": "2026-06-26T12:21:22.543162+00:00",
+  "git_commit": "8bd046a3c3b128e8190dbb54d76a54cd6b9282a3",
+  "input_paths": [
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/rationale_only/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_only/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_plus_rationale/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/rationale_scrambled/rankings.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank/answer_scrambled/rankings.csv"
+  ],
+  "output_paths": [
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/summary.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/paired_contrasts.csv",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/paired_top1_deltas.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_overall_top1_top2.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_by_stratum_top1.png"
+  ],
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+}

data/external/evidence/formal/prospective_diffusion_perturbation/figures/prompt_mode_by_stratum_top1.metadata.json

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+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/paired_top1_deltas.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_overall_top1_top2.png",
+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_by_stratum_top1.png"
+  ],
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data/external/evidence/formal/prospective_diffusion_perturbation/figures/prompt_mode_overall_top1_top2.metadata.json

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+    "results/formal/prospective_diffusion_perturbation/llm_rerank_analysis/figures/prompt_mode_by_stratum_top1.png"
+  ],
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+by_benchmark_generator_stratum,gpqa,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,688,688,0.6860465116,0.6744186047,0.01162790698,-0.07728860121,0.1005881222,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.5125,0.525,-0.0125,-0.125,0.1,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.525,0.525,0,-0.125,0.1125,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,1091,1091,0.8799266728,0.9239230064,-0.04399633364,-0.1011049939,0.01076330055,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.85,0.9,-0.05,-0.125,0.025,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.85,0.9,-0.05,-0.125,0.025,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,668,668,0.4401197605,0.369760479,0.07035928144,-0.007486441145,0.1484412728,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.1875,0.225,-0.0375,-0.1125,0.0253125,2000,1729
+by_benchmark_generator_stratum,gpqa,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.225,0.25,-0.025,-0.1125,0.0625,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,73,606,606,0.8448844884,0.8052805281,0.0396039604,-0.03733766234,0.1164969737,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,73,0,0,0.7260273973,0.698630137,0.02739726027,-0.05479452055,0.1232876712,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,73,0,0,0.7397260274,0.698630137,0.04109589041,-0.05479452055,0.1369863014,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,693,693,0.8051948052,0.8095238095,-0.004329004329,-0.0752175797,0.06872974803,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.6625,0.7375,-0.075,-0.1753125,0.025,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.7,0.75,-0.05,-0.15,0.05,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,655,655,0.720610687,0.7770992366,-0.05648854962,-0.1242517483,0.001651320803,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.55,0.6625,-0.1125,-0.2125,-0.025,2000,1729
+by_benchmark_generator_stratum,gpqa,mimo,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.6125,0.675,-0.0625,-0.1625,0.025,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,631,631,0.5483359746,0.4167987322,0.1315372425,0.04100784918,0.217397922,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.2875,0.125,0.1625,0.05,0.275,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,boundary,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.35,0.175,0.175,0.075,0.275,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,876,876,0.7100456621,0.6621004566,0.04794520548,-0.05436900056,0.1511284212,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.5,0.4875,0.0125,-0.125,0.1378125,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,high_potential,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.55,0.5125,0.0375,-0.075,0.15,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,rank_auc,80,580,580,0.3517241379,0.2120689655,0.1396551724,0.07179487179,0.2172413793,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top1_correct,80,0,0,0.1,0.05,0.05,-0.025,0.125,2000,1729
+by_benchmark_generator_stratum,hle_text_mc,deepseek,natural,low_availability,rationale_increment_over_answer,answer_plus_rationale,answer_only,top2_correct,80,0,0,0.1625,0.075,0.0875,0,0.175,2000,1729

data/external/results/formal/README.md

@@ -0,0 +1,23 @@
+# Formal Results
+
+Registered fresh experiment outputs and NMI work-package artifacts belong here.
+Use `results/formal/experiments/<experiment_id>/summary.csv` and
+`details.csv` for claim-bearing fresh runs. Each artifact should have a sibling
+`.metadata.json` sidecar generated by the CLI.
+
+Do not place smoke or exploratory pilot outputs in this directory.
+
+## Formal Diagnostic Snapshots
+
+- `hle_qa_selector_boundary/`: HLE open-answer selector-boundary diagnostic.
+  It is formalized separately from the five-benchmark selector-boundary
+  snapshot because HLE QA uses LLM-equivalence labels for open-text answers.
+- `global_leaderboard_ranking_completion/`: Supplemental formal natural-pool
+  ranking overlay used by the complete frozen natural-pool replay.
+- `global_leaderboard_diffusion/`: Formal complete frozen natural-pool replay
+  summary package. Raw replay trace details remain excluded because they are a
+  large intermediate artifact.
+- `global_leaderboard_pool_size_cost_efficiency/`: Formal pool-size sensitivity
+  and paid-equivalent cost-efficiency package for the 2x2 generator-selector
+  matrix. Full selector-ranking traces are retained under model-stratified
+  directories.