Archive Qwen3.7-Max and DeepSeek V4 Pro paired results

results/README.md

@@ -8,6 +8,8 @@
 | Claude Opus 4.8 | [1,000 题](claude-opus-4-8/baseline/) | [1,000 题](claude-opus-4-8/deepagents/) |
 | Kimi K3 | [1,000 题](kimi-k3/baseline/) | [1,000 题](kimi-k3/deepagents/) |
 | Gemini 3.1 Pro Preview | [1,000 题](gemini-3.1-pro-preview/baseline/) | [1,000 题](gemini-3.1-pro-preview/deepagents/) |
+| Qwen3.7-Max | [1,000 题](qwen3.7-max/baseline/) | [1,000 题](qwen3.7-max/deepagents/) |
+| DeepSeek V4 Pro | [1,000 题](deepseek-v4-pro/baseline/) | [1,000 题](deepseek-v4-pro/deepagents/) |
 
 这里先保存完成的实验产物。页面仍只读取根目录 `/results.csv`，本次没有更新它或修改页面代码。等各模型结果齐备，再核对数据、评分和协议后统一整理正式榜单。
 
@@ -22,3 +24,11 @@
 K3 保留两组 5 / 4 条任务 unknown，Gemini 无任务 unknown；每组固定 1,000 题分母。指标级 null 与任务级 unknown 分别记账。新增记录的原始预测不在源评分快照中，prediction 字段因此留空并带有导出状态标记；不把导出缺失解释为模型未生成预测。详细协议、源版本、阶段诊断和核验范围见各模型目录。
 
 运行 `python3 -B results/verify_kimi_gemini.py` 可检查归档清单、4,000 条新增逐题记录及 36 项指标汇总；这是离线导出核验，不是重新运行实验或官方 scorer 一致性认证。
+
+## Qwen3.7-Max 与 DeepSeek V4 Pro
+
+新增四组、4,000 条记录后，存档覆盖六个模型、12 组、12,000 条记录。GPT-5.5 不在本次范围。
+
+Qwen3.7-Max 原生完整复现率为 19.8% / 24.8%，DeepSeek V4 Pro 为 12.9% / 18.3%；本地 HF 四维与原生五维分开保存。Qwen DeepAgents 保留 6 条任务 unknown 和 task 453 的 1 条 invalid evidence：999 条有效封存、1 条无效证据，共 1,000 个固定题号。无效证据不标为失败或有效封存，指标均为空；未重跑或删除。DeepSeek 双组没有任务 unknown 或 invalid。
+
+运行 `python3 -B results/verify_qwen_deepseek.py` 可核对新增四组逐题记录、配对表、36 项汇总和归档清单。这是已接受产物的离线导出验证，不代表重新进行原生审计或官方评分。网页根目录 results.csv 与页面代码由后续网页更新单独处理。

results/deepseek-v4-pro/baseline/README.md

@@ -0,0 +1,11 @@
+# DeepSeek V4 Pro / baseline
+
+固定 1,000 题：成功 277、确定失败 723、任务 unknown 0、invalid evidence 0。已封存 1000 条；无待开始或在途记录。原生完整复现率 12.9%。
+
+`results.jsonl` 与 `results.csv` 保存逐题状态、指标、用量和结果哈希；`summary.json` 分别保存本地 HF 四维和 local-paper-v1 五维；`config.json` 保存任务清单、协议、源代码版本和接续来源。上一级含配对表、来源与导出核验。
+
+`resolved` 仅表示有效封存，`definite_outcome` 表示成功或确定失败。任务 unknown、无效证据与指标 null 分开保留，均不从 1,000 的分母移除。无效记录仅有 `unverified_result_sha256`，不可当作有效执行结果。后续阶段 pending 可能表示前序失败后没有执行到，不表示任务仍待派发。
+
+原始预测三元组不在源评分快照中，prediction 字段为空，并有明确导出状态；不能据此认为所有模型都没有生成预测。配对比较含历史协议修订，非严格等预算因果实验。本地评分尚未核实官方一致性。
+
+本次仅归档已接受的评分和状态，没有重新执行模型或程序。不包含 benchmark 输入、隐藏答案、原始提示词/API 轨迹、凭据或机器路径。

results/deepseek-v4-pro/baseline/config.json

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+{
+  "schema_version": 2,
+  "model": "deepseek-v4-pro",
+  "arm": "baseline",
+  "harness": "none",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "dataset": {
+    "repo_id": "CamoAiLab/InferenceNet",
+    "revision": "59f9512a38e594528807744214a60ee00367434e",
+    "task_directory": "Selected_1000",
+    "task_list": "Selected_1000/1000_new.csv",
+    "prior_results_imported": false,
+    "engineering_pilot": false,
+    "expected_tasks": 1000,
+    "task_ids": [
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+          "memory": "6g",
+          "tmpfs": "256m"
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+        "memory_enforcement": "RLIMIT_AS",
+        "single_payload_process": true,
+        "network": "none",
+        "uid": 10001,
+        "capacity_profile": "independent-six-slots-20260916",
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+        "revision": "59f9512a38e594528807744214a60ee00367434e",
+        "task_directory": "Selected_1000",
+        "task_list": "Selected_1000/1000_new.csv",
+        "prior_results_imported": false,
+        "engineering_pilot": false
+      },
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+        "protocol": "inferencenet-dsw-amd64-single-process-v3",
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+          "tmpfs": "256m"
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+        "memory_enforcement": "RLIMIT_AS",
+        "single_payload_process": true,
+        "network": "none",
+        "uid": 10001
+      },
+      "source_commit": "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
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+      },
+      "origin": "parent"
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+  ],
+  "selected_origin_counts": {
+    "child": 999,
+    "parent": 1
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+  "source_commits": [
+    "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
+    "9d6a89eb6c4e42fab8c14b768d1bc4e40f15f980"
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+  "result_snapshot_sha256": "eff050fe7977423fdffc731fc62b9ea45652743d2f3184931ae70c3b9365d176",
+  "official_parity_verified": false,
+  "notes": [
+    "Historical disjoint parent/child continuation; original source and protocol hashes retained.",
+    "Different baseline/harness call budgets; not an equal-cost causal comparison.",
+    "Unknown and invalid evidence remain in the denominator; no replacement or rescoring.",
+    "Invalid evidence is not sealed; its unverified hash is distinct from a verified result hash."
+  ]
+}

results/deepseek-v4-pro/baseline/summary.json

@@ -0,0 +1,191 @@
+{
+  "schema_version": 2,
+  "kind": "inferencenet-offline-leaderboard-export",
+  "generated_at": "2026-09-16T17:18:47.373930+00:00",
+  "model": "deepseek-v4-pro",
+  "arm": "baseline",
+  "metric_profile": "hf-leaderboard-v1",
+  "definitions": {
+    "compilation_success": "Trusted evidence of complete code execution; no prediction JSON gate.",
+    "partial_replication": "Coefficient relative error <= .05; no standard-error or p-value gate.",
+    "coefficient_direction": "Matching strictly positive or strictly negative coefficient signs.",
+    "significance_level": "Equal p-value category: p < .01, p < .05, p < .1, otherwise; no direction gate."
+  },
+  "assumptions": {
+    "official_rules": "Webpage interpretation only; official scorer parity is not verified.",
+    "compilation_evidence": "Caller supplies True, False, or None from verified execution evidence, including exit status, timeout, termination confirmation, and execution errors. Missing or uncertain evidence maps to None.",
+    "prediction_evidence": "Only execution_status=succeeded and scoring_status=scored rows are evaluated. The current caller requires a complete valid prediction triplet; invalid outputs are not recovered here.",
+    "coefficient_boundary": "5% includes equality. Numeric decimal representations are compared exactly without epsilon.",
+    "zero_reference_coefficient": "A zero reference coefficient is unknown for relative error and positive/negative direction; it does not block significance. A zero prediction against a nonzero reference is incorrect.",
+    "significance_categories": "Four categories use strict .01, .05, and .1 boundaries. Both p-values must be numeric and within [0, 1]. These boundaries and the absent direction gate are explicit local choices.",
+    "field_validation": "Each metric requires only its own finite numeric fields. Booleans, numeric strings, and inequalities are not coerced. Standard errors do not affect any of these three formulas.",
+    "denominator": "All planned tasks remain in every denominator. Confirmed compilation failures are False; missing or uncertain execution evidence is unknown. For the three result metrics, failed execution, missing predictions, unscored rows, and unsupported reference fields are unknown. Unknowns contribute no successes and are counted separately.",
+    "attempt_selection": "The caller supplies one row per task under its frozen attempt policy."
+  },
+  "official_parity_verified": false,
+  "evidence_class": "amended_comparison",
+  "original_protocol_complete": false,
+  "complete": true,
+  "all_slots_sealed": true,
+  "dataset_revision": "59f9512a38e594528807744214a60ee00367434e",
+  "included_in_displayed_leaderboard": false,
+  "publication_kind": "results_archive",
+  "result": {
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+        "coverage_percent": 100.0
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+      }
+    },
+    "row": {
+      "Model ID": "deepseek-v4-pro baseline",
+      "Compilation Success": 28.1,
+      "Partial Replication": 19.5,
+      "Correct Coefficient Direction": 26.0,
+      "Significant Level Correctness": 23.6
+    },
+    "columns": [
+      "Model ID",
+      "Compilation Success",
+      "Partial Replication",
+      "Correct Coefficient Direction",
+      "Significant Level Correctness"
+    ],
+    "expected_count": 1000,
+    "resolved_count": 1000,
+    "sealed_count": 1000,
+    "definite_outcome_count": 1000,
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+      "completed": 1000,
+      "planned": 1000
+    }
+  },
+  "legacy_local_paper": {
+    "profile": "local-paper-v1",
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+      "partial": "coefficient and SE relative errors < .05; no p gate; includes perfect",
+      "coefficient_only": "coefficient relative error <= .05",
+      "direction": "matching strictly positive or strictly negative coefficient signs",
+      "significance": "direction and equal category: p < .01, p < .05, p < .1, otherwise"
+    },
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+      },
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+      },
+      "direction": {
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+        "assessable": 277,
+        "coverage_percent": 27.7
+      }
+    }
+  },
+  "verification_scope": "Offline equality to accepted flags, hashes and states; raw predictions unavailable; not a fresh native audit or official scorer parity check.",
+  "usage": {
+    "sealed_model_calls": 1000,
+    "unknown_usage_calls": 0,
+    "unsealed_episodes_excluded": 0,
+    "invalid_evidence_episodes_excluded": 0,
+    "known_token_subtotal": {
+      "input_tokens": 421568,
+      "output_tokens": 3425749,
+      "total_tokens": 3847317
+    },
+    "unknown_by_field": {
+      "input_tokens": 0,
+      "output_tokens": 0,
+      "total_tokens": 0
+    },
+    "total_tokens_complete": true,
+    "usd": null,
+    "usd_status": "unknown_no_verified_price_or_billing_receipt",
+    "summed_episode_seconds": 109668.68000000007
+  }
+}

results/deepseek-v4-pro/deepagents/README.md

@@ -0,0 +1,11 @@
+# DeepSeek V4 Pro / deepagents
+
+固定 1,000 题：成功 352、确定失败 648、任务 unknown 0、invalid evidence 0。已封存 1000 条；无待开始或在途记录。原生完整复现率 18.3%。
+
+`results.jsonl` 与 `results.csv` 保存逐题状态、指标、用量和结果哈希；`summary.json` 分别保存本地 HF 四维和 local-paper-v1 五维；`config.json` 保存任务清单、协议、源代码版本和接续来源。上一级含配对表、来源与导出核验。
+
+`resolved` 仅表示有效封存，`definite_outcome` 表示成功或确定失败。任务 unknown、无效证据与指标 null 分开保留，均不从 1,000 的分母移除。无效记录仅有 `unverified_result_sha256`，不可当作有效执行结果。后续阶段 pending 可能表示前序失败后没有执行到，不表示任务仍待派发。
+
+原始预测三元组不在源评分快照中，prediction 字段为空，并有明确导出状态；不能据此认为所有模型都没有生成预测。配对比较含历史协议修订，非严格等预算因果实验。本地评分尚未核实官方一致性。
+
+本次仅归档已接受的评分和状态，没有重新执行模型或程序。不包含 benchmark 输入、隐藏答案、原始提示词/API 轨迹、凭据或机器路径。

results/deepseek-v4-pro/deepagents/config.json

@@ -0,0 +1,1199 @@
+{
+  "schema_version": 2,
+  "model": "deepseek-v4-pro",
+  "arm": "deepagents",
+  "harness": "DeepAgents 0.7.13",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "dataset": {
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+    "revision": "59f9512a38e594528807744214a60ee00367434e",
+    "task_directory": "Selected_1000",
+    "task_list": "Selected_1000/1000_new.csv",
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+    "Different baseline/harness call budgets; not an equal-cost causal comparison.",
+    "Unknown and invalid evidence remain in the denominator; no replacement or rescoring.",
+    "Invalid evidence is not sealed; its unverified hash is distinct from a verified result hash."
+  ]
+}

results/deepseek-v4-pro/deepagents/summary.json

@@ -0,0 +1,191 @@
+{
+  "schema_version": 2,
+  "kind": "inferencenet-offline-leaderboard-export",
+  "generated_at": "2026-09-16T17:18:47.373930+00:00",
+  "model": "deepseek-v4-pro",
+  "arm": "deepagents",
+  "metric_profile": "hf-leaderboard-v1",
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+    "partial_replication": "Coefficient relative error <= .05; no standard-error or p-value gate.",
+    "coefficient_direction": "Matching strictly positive or strictly negative coefficient signs.",
+    "significance_level": "Equal p-value category: p < .01, p < .05, p < .1, otherwise; no direction gate."
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+  "assumptions": {
+    "official_rules": "Webpage interpretation only; official scorer parity is not verified.",
+    "compilation_evidence": "Caller supplies True, False, or None from verified execution evidence, including exit status, timeout, termination confirmation, and execution errors. Missing or uncertain evidence maps to None.",
+    "prediction_evidence": "Only execution_status=succeeded and scoring_status=scored rows are evaluated. The current caller requires a complete valid prediction triplet; invalid outputs are not recovered here.",
+    "coefficient_boundary": "5% includes equality. Numeric decimal representations are compared exactly without epsilon.",
+    "zero_reference_coefficient": "A zero reference coefficient is unknown for relative error and positive/negative direction; it does not block significance. A zero prediction against a nonzero reference is incorrect.",
+    "significance_categories": "Four categories use strict .01, .05, and .1 boundaries. Both p-values must be numeric and within [0, 1]. These boundaries and the absent direction gate are explicit local choices.",
+    "field_validation": "Each metric requires only its own finite numeric fields. Booleans, numeric strings, and inequalities are not coerced. Standard errors do not affect any of these three formulas.",
+    "denominator": "All planned tasks remain in every denominator. Confirmed compilation failures are False; missing or uncertain execution evidence is unknown. For the three result metrics, failed execution, missing predictions, unscored rows, and unsupported reference fields are unknown. Unknowns contribute no successes and are counted separately.",
+    "attempt_selection": "The caller supplies one row per task under its frozen attempt policy."
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+  "evidence_class": "amended_comparison",
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+      }
+    },
+    "row": {
+      "Model ID": "deepseek-v4-pro deepagents",
+      "Compilation Success": 35.2,
+      "Partial Replication": 27.0,
+      "Correct Coefficient Direction": 33.8,
+      "Significant Level Correctness": 30.8
+    },
+    "columns": [
+      "Model ID",
+      "Compilation Success",
+      "Partial Replication",
+      "Correct Coefficient Direction",
+      "Significant Level Correctness"
+    ],
+    "expected_count": 1000,
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+      "completed": 1000,
+      "planned": 1000
+    }
+  },
+  "legacy_local_paper": {
+    "profile": "local-paper-v1",
+    "definitions": {
+      "perfect": "coefficient and SE relative errors <= .01 and p absolute error <= .01",
+      "partial": "coefficient and SE relative errors < .05; no p gate; includes perfect",
+      "coefficient_only": "coefficient relative error <= .05",
+      "direction": "matching strictly positive or strictly negative coefficient signs",
+      "significance": "direction and equal category: p < .01, p < .05, p < .1, otherwise"
+    },
+    "metrics": {
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+        "unknown_count": 648,
+        "failure_count": 53,
+        "assessable": 352,
+        "coverage_percent": 35.2
+      }
+    }
+  },
+  "verification_scope": "Offline equality to accepted flags, hashes and states; raw predictions unavailable; not a fresh native audit or official scorer parity check.",
+  "usage": {
+    "sealed_model_calls": 5812,
+    "unknown_usage_calls": 0,
+    "unsealed_episodes_excluded": 0,
+    "invalid_evidence_episodes_excluded": 0,
+    "known_token_subtotal": {
+      "input_tokens": 35729626,
+      "output_tokens": 3614764,
+      "total_tokens": 39344390
+    },
+    "unknown_by_field": {
+      "input_tokens": 0,
+      "output_tokens": 0,
+      "total_tokens": 0
+    },
+    "total_tokens_complete": true,
+    "usd": null,
+    "usd_status": "unknown_no_verified_price_or_billing_receipt",
+    "summed_episode_seconds": 218448.4960000001
+  }
+}

results/deepseek-v4-pro/diagnostics.json

@@ -0,0 +1,47 @@
+{
+  "stage_counts": {
+    "baseline": [
+      {
+        "generation": "succeeded",
+        "execution": "failed",
+        "scoring": "pending",
+        "count": 723
+      },
+      {
+        "generation": "succeeded",
+        "execution": "succeeded",
+        "scoring": "scored",
+        "count": 277
+      }
+    ],
+    "deepagents": [
+      {
+        "generation": "failed",
+        "execution": "pending",
+        "scoring": "pending",
+        "count": 635
+      },
+      {
+        "generation": "succeeded",
+        "execution": "succeeded",
+        "scoring": "scored",
+        "count": 352
+      },
+      {
+        "generation": "succeeded",
+        "execution": "failed",
+        "scoring": "pending",
+        "count": 13
+      }
+    ]
+  },
+  "task_unknown_ids": {
+    "baseline": [],
+    "deepagents": []
+  },
+  "invalid_evidence_ids": {
+    "baseline": [],
+    "deepagents": []
+  },
+  "raw_error_reasons_verified": false
+}

results/deepseek-v4-pro/export-verification.json

@@ -0,0 +1,44 @@
+{
+  "status": "passed_offline",
+  "per_arm": {
+    "baseline": {
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+      },
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+      "all_slots_sealed": true,
+      "metrics_recomputed": 9,
+      "matches_accepted_flags_states_hashes": true
+    },
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+      },
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+      "all_slots_sealed": true,
+      "metrics_recomputed": 9,
+      "matches_accepted_flags_states_hashes": true
+    }
+  },
+  "paired_rows": 1000,
+  "metrics_recomputed": 18,
+  "official_parity_verified": false
+}

results/deepseek-v4-pro/provenance.json

@@ -0,0 +1,42 @@
+{
+  "model": "deepseek-v4-pro",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "result_snapshot_sha256": "eff050fe7977423fdffc731fc62b9ea45652743d2f3184931ae70c3b9365d176",
+  "accepted_results_sha256": "dd72f352be1895b11914dd2aea1fdceb21c453932877c588ecaf81ec09861105",
+  "accepted_task_records_sha256": "32a797b4da8dfe90d44b37d7715fe726a29c5b4f93a1b24d7d5ffbffb81e9749",
+  "record_count": 2000,
+  "selected_task_count": 1000,
+  "source_commits": [
+    "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
+    "9d6a89eb6c4e42fab8c14b768d1bc4e40f15f980"
+  ],
+  "historical_native_audit": {
+    "mode": "historical_final_cache",
+    "snapshot_sha256": "7de17ac129bbb07ac7d1fa08adb92642eeb7cfadab4d4a68946661308d8adde1",
+    "journal_sha256": "d35e92010e0f85de995ef587f3d64616260a70600be6749644c33fb287d1a32b",
+    "acceptance_sha256": "8ae98f599a7874a5c5f5c30c2cd735ad074a2790efe0c726c0e06c2686b27b94",
+    "collector_sha256": "7963b4fd6ef312307d5471d031e6851429f139b03a3e6d7ffc7ca9bd44d98c89",
+    "renderer_sha256": "b2cb2f0ae0523431e3be13ac23a6730c8e6a511e7c645921dea79a1cacffe2fd",
+    "started_at": "2026-09-16T01:01:30.976377+00:00",
+    "finished_at": "2026-09-16T02:24:03.769359+00:00",
+    "model_sha256": "1ea1971a9930edbc23942fdcc07bd847b9de00b90d5e9245618b03a02e49c302",
+    "source_checkpoint": {
+      "record_sha256": "b607ce017fbb746b127d6cbd9a09edbbd43d9e57e6e20d448c32895ff38b2fe7",
+      "record_bytes": 4406227
+    },
+    "current_identity_check": {
+      "kind": "current_source_core_result_hashes_parent_absence",
+      "started_at": "2026-09-16T07:43:01.435804+00:00",
+      "finished_at": "2026-09-16T07:43:33.877870+00:00",
+      "result_hashes_checked": 2000,
+      "absent_parent_slots_checked": 1998,
+      "native_artifacts_reaudited": false,
+      "input_blobs_rehashed": false
+    },
+    "native_audit_scope": "Historical native artifact/execution/scoring verification; input blobs were not rehashed by that collector."
+  },
+  "official_parity_verified": false,
+  "new_model_calls": 0,
+  "new_benchmark_executions": 0,
+  "verification_scope": "Offline equality and metric reaggregation of accepted score exports. No fresh input/native audit; no raw prediction rescoring."
+}

results/index.json

@@ -51,7 +51,31 @@
       "arm": "deepagents",
       "rows": 1000,
       "path": "results/gemini-3.1-pro-preview/deepagents"
+    },
+    {
+      "model": "qwen3.7-max",
+      "arm": "baseline",
+      "rows": 1000,
+      "path": "results/qwen3.7-max/baseline"
+    },
+    {
+      "model": "qwen3.7-max",
+      "arm": "deepagents",
+      "rows": 1000,
+      "path": "results/qwen3.7-max/deepagents"
+    },
+    {
+      "model": "deepseek-v4-pro",
+      "arm": "baseline",
+      "rows": 1000,
+      "path": "results/deepseek-v4-pro/baseline"
+    },
+    {
+      "model": "deepseek-v4-pro",
+      "arm": "deepagents",
+      "rows": 1000,
+      "path": "results/deepseek-v4-pro/deepagents"
     }
   ],
-  "updated_at_utc": "2026-09-16T15:28:00.953066+00:00"
+  "updated_at_utc": "2026-09-16T17:18:47.373930+00:00"
 }

results/manifest.sha256

@@ -1,4 +1,4 @@
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 2ad22f4778525b1460f1857e1095f2eea5620063fba1ffa6314ca7fd50f14703  claude-opus-4-8/baseline/README.md
 8058afcd14c34d666277c0f32ac5962398b10618df5b1aa0e13cd9862344dc56  claude-opus-4-8/baseline/config.json
 4d5f859e472b79195c9be6b1f0e9c5feecf59a81dfe32ac08eb4c1d4967ed98e  claude-opus-4-8/baseline/results.csv
@@ -9,6 +9,20 @@ dfb00967c2a2ff320d5a6d8c142cbc6ef37d4fb144abcc7a451673515c2b4c50  claude-opus-4-
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 f86da9c76f8becb75b4970c486160013209a6aa4239923018b217e55f1b0a614  claude-opus-4-8/deepagents/summary.json
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@@ -33,7 +47,7 @@ a3e24175f2395cffbbcd6d9d3c89689bd3a3b22dd4ce61bb78d5da33c6b6cc1b  gpt-5.6-sol/de
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-2b6c21661ef74f692d64095f1e3fd64f9e696cd9876b5186810ed340aff0c24e  index.json
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 f87d2dd3b390695f6b420a78e126b504abc3d292180a3443deaead174ec1b464  kimi-k3/baseline/results.csv
@@ -48,4 +62,19 @@ bfaac06563fc53d5f564197fdfb69e24ddbdff622b85d67bbf2a13fb7fb5d9ba  kimi-k3/diagno
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 06ed669caaba3ca5e252d12af3de32223019d50aefd9c46751ca3cb35110fce2  verify_kimi_gemini.py
+9c6d1d6b44998a459141969065e4e23fb0126b3556074ce35803f970ce8c0869  verify_qwen_deepseek.py

results/qwen3.7-max/baseline/README.md

@@ -0,0 +1,11 @@
+# Qwen3.7-Max / baseline
+
+固定 1,000 题：成功 483、确定失败 517、任务 unknown 0、invalid evidence 0。已封存 1000 条；无待开始或在途记录。原生完整复现率 19.8%。
+
+`results.jsonl` 与 `results.csv` 保存逐题状态、指标、用量和结果哈希；`summary.json` 分别保存本地 HF 四维和 local-paper-v1 五维；`config.json` 保存任务清单、协议、源代码版本和接续来源。上一级含配对表、来源与导出核验。
+
+`resolved` 仅表示有效封存，`definite_outcome` 表示成功或确定失败。任务 unknown、无效证据与指标 null 分开保留，均不从 1,000 的分母移除。无效记录仅有 `unverified_result_sha256`，不可当作有效执行结果。后续阶段 pending 可能表示前序失败后没有执行到，不表示任务仍待派发。
+
+原始预测三元组不在源评分快照中，prediction 字段为空，并有明确导出状态；不能据此认为所有模型都没有生成预测。配对比较含历史协议修订，非严格等预算因果实验。本地评分尚未核实官方一致性。
+
+本次仅归档已接受的评分和状态，没有重新执行模型或程序。不包含 benchmark 输入、隐藏答案、原始提示词/API 轨迹、凭据或机器路径。

results/qwen3.7-max/baseline/config.json

@@ -0,0 +1,1199 @@
+{
+  "schema_version": 2,
+  "model": "qwen3.7-max",
+  "arm": "baseline",
+  "harness": "none",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "dataset": {
+    "repo_id": "CamoAiLab/InferenceNet",
+    "revision": "59f9512a38e594528807744214a60ee00367434e",
+    "task_directory": "Selected_1000",
+    "task_list": "Selected_1000/1000_new.csv",
+    "prior_results_imported": false,
+    "engineering_pilot": false,
+    "expected_tasks": 1000,
+    "task_ids": [
+      1,
+      2,
+      3,
+      4,
+      5,
+      6,
+      7,
+      8,
+      9,
+      10,
+      11,
+      12,
+      13,
+      14,
+      15,
+      16,
+      17,
+      18,
+      19,
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+        "prior_results_imported": false,
+        "engineering_pilot": false
+      },
+      "execution_identity": {
+        "backend": "dsw-bwrap-v3",
+        "protocol": "inferencenet-dsw-amd64-single-process-v3",
+        "deployment_sha256": "6c7d0c001925f436f884ebb737c430c4644b54fc17dcc681320133cca34a4bee",
+        "rootfs_inventory_sha256": "9ac222dbc0ea58880e790c36f5afddddb727f948e23e73cf0978de73ae498e59",
+        "engine_memory_bytes": 12884901888,
+        "engine_cpus": 4,
+        "cpu_slots": [
+          [
+            16,
+            17
+          ],
+          [
+            18,
+            19
+          ]
+        ],
+        "resources": {
+          "memory": "6g",
+          "cpus": 2.0,
+          "tmpfs": "256m"
+        },
+        "memory_enforcement": "RLIMIT_AS",
+        "single_payload_process": true,
+        "network": "none",
+        "uid": 10001
+      },
+      "source_commit": "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
+      "scorer_sha256": {
+        "eval/evaluation/metrics.py": "52d46989ab6dc8b4726edfc281a0e27c9f57dce3a958b7de73143aec47d81a61",
+        "eval/evaluation/leaderboard.py": "f6a6190e97f8bf5c499e97de74f0b882ebb8322dea92e0543711d523ffe6cba3"
+      },
+      "origin": "parent"
+    }
+  ],
+  "selected_origin_counts": {
+    "child": 993,
+    "parent": 7
+  },
+  "source_commits": [
+    "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
+    "9d6a89eb6c4e42fab8c14b768d1bc4e40f15f980"
+  ],
+  "result_snapshot_sha256": "eff050fe7977423fdffc731fc62b9ea45652743d2f3184931ae70c3b9365d176",
+  "official_parity_verified": false,
+  "notes": [
+    "Historical disjoint parent/child continuation; original source and protocol hashes retained.",
+    "Different baseline/harness call budgets; not an equal-cost causal comparison.",
+    "Unknown and invalid evidence remain in the denominator; no replacement or rescoring.",
+    "Invalid evidence is not sealed; its unverified hash is distinct from a verified result hash."
+  ]
+}

results/qwen3.7-max/baseline/summary.json

@@ -0,0 +1,191 @@
+{
+  "schema_version": 2,
+  "kind": "inferencenet-offline-leaderboard-export",
+  "generated_at": "2026-09-16T17:18:47.373930+00:00",
+  "model": "qwen3.7-max",
+  "arm": "baseline",
+  "metric_profile": "hf-leaderboard-v1",
+  "definitions": {
+    "compilation_success": "Trusted evidence of complete code execution; no prediction JSON gate.",
+    "partial_replication": "Coefficient relative error <= .05; no standard-error or p-value gate.",
+    "coefficient_direction": "Matching strictly positive or strictly negative coefficient signs.",
+    "significance_level": "Equal p-value category: p < .01, p < .05, p < .1, otherwise; no direction gate."
+  },
+  "assumptions": {
+    "official_rules": "Webpage interpretation only; official scorer parity is not verified.",
+    "compilation_evidence": "Caller supplies True, False, or None from verified execution evidence, including exit status, timeout, termination confirmation, and execution errors. Missing or uncertain evidence maps to None.",
+    "prediction_evidence": "Only execution_status=succeeded and scoring_status=scored rows are evaluated. The current caller requires a complete valid prediction triplet; invalid outputs are not recovered here.",
+    "coefficient_boundary": "5% includes equality. Numeric decimal representations are compared exactly without epsilon.",
+    "zero_reference_coefficient": "A zero reference coefficient is unknown for relative error and positive/negative direction; it does not block significance. A zero prediction against a nonzero reference is incorrect.",
+    "significance_categories": "Four categories use strict .01, .05, and .1 boundaries. Both p-values must be numeric and within [0, 1]. These boundaries and the absent direction gate are explicit local choices.",
+    "field_validation": "Each metric requires only its own finite numeric fields. Booleans, numeric strings, and inequalities are not coerced. Standard errors do not affect any of these three formulas.",
+    "denominator": "All planned tasks remain in every denominator. Confirmed compilation failures are False; missing or uncertain execution evidence is unknown. For the three result metrics, failed execution, missing predictions, unscored rows, and unsupported reference fields are unknown. Unknowns contribute no successes and are counted separately.",
+    "attempt_selection": "The caller supplies one row per task under its frozen attempt policy."
+  },
+  "official_parity_verified": false,
+  "evidence_class": "amended_comparison",
+  "original_protocol_complete": false,
+  "complete": true,
+  "all_slots_sealed": true,
+  "dataset_revision": "59f9512a38e594528807744214a60ee00367434e",
+  "included_in_displayed_leaderboard": false,
+  "publication_kind": "results_archive",
+  "result": {
+    "metrics": {
+      "compilation_success": {
+        "count": 486,
+        "denominator": 1000,
+        "rate": 0.486,
+        "score": 48.6,
+        "unknown_count": 0,
+        "failure_count": 514,
+        "assessable": 1000,
+        "coverage_percent": 100.0
+      },
+      "partial_replication": {
+        "count": 315,
+        "denominator": 1000,
+        "rate": 0.315,
+        "score": 31.5,
+        "unknown_count": 518,
+        "failure_count": 167,
+        "assessable": 482,
+        "coverage_percent": 48.2
+      },
+      "coefficient_direction": {
+        "count": 454,
+        "denominator": 1000,
+        "rate": 0.454,
+        "score": 45.4,
+        "unknown_count": 518,
+        "failure_count": 28,
+        "assessable": 482,
+        "coverage_percent": 48.2
+      },
+      "significance_level": {
+        "count": 396,
+        "denominator": 1000,
+        "rate": 0.396,
+        "score": 39.6,
+        "unknown_count": 518,
+        "failure_count": 86,
+        "assessable": 482,
+        "coverage_percent": 48.2
+      }
+    },
+    "row": {
+      "Model ID": "qwen3.7-max baseline",
+      "Compilation Success": 48.6,
+      "Partial Replication": 31.5,
+      "Correct Coefficient Direction": 45.4,
+      "Significant Level Correctness": 39.6
+    },
+    "columns": [
+      "Model ID",
+      "Compilation Success",
+      "Partial Replication",
+      "Correct Coefficient Direction",
+      "Significant Level Correctness"
+    ],
+    "expected_count": 1000,
+    "resolved_count": 1000,
+    "sealed_count": 1000,
+    "definite_outcome_count": 1000,
+    "task_unknown_count": 0,
+    "invalid_evidence_count": 0,
+    "valid_prediction_count": 483,
+    "task_counts": {
+      "succeeded": 483,
+      "failed": 517,
+      "unknown": 0,
+      "unsealed": 0,
+      "not_started": 0,
+      "invalid_evidence": 0,
+      "completed": 1000,
+      "planned": 1000
+    }
+  },
+  "legacy_local_paper": {
+    "profile": "local-paper-v1",
+    "definitions": {
+      "perfect": "coefficient and SE relative errors <= .01 and p absolute error <= .01",
+      "partial": "coefficient and SE relative errors < .05; no p gate; includes perfect",
+      "coefficient_only": "coefficient relative error <= .05",
+      "direction": "matching strictly positive or strictly negative coefficient signs",
+      "significance": "direction and equal category: p < .01, p < .05, p < .1, otherwise"
+    },
+    "metrics": {
+      "perfect": {
+        "count": 198,
+        "denominator": 1000,
+        "rate": 0.198,
+        "score": 19.8,
+        "unknown_count": 519,
+        "failure_count": 283,
+        "assessable": 481,
+        "coverage_percent": 48.1
+      },
+      "partial": {
+        "count": 238,
+        "denominator": 1000,
+        "rate": 0.238,
+        "score": 23.8,
+        "unknown_count": 519,
+        "failure_count": 243,
+        "assessable": 481,
+        "coverage_percent": 48.1
+      },
+      "coefficient_only": {
+        "count": 315,
+        "denominator": 1000,
+        "rate": 0.315,
+        "score": 31.5,
+        "unknown_count": 519,
+        "failure_count": 166,
+        "assessable": 481,
+        "coverage_percent": 48.1
+      },
+      "direction": {
+        "count": 453,
+        "denominator": 1000,
+        "rate": 0.453,
+        "score": 45.3,
+        "unknown_count": 519,
+        "failure_count": 28,
+        "assessable": 481,
+        "coverage_percent": 48.1
+      },
+      "significance": {
+        "count": 380,
+        "denominator": 1000,
+        "rate": 0.38,
+        "score": 38.0,
+        "unknown_count": 519,
+        "failure_count": 101,
+        "assessable": 481,
+        "coverage_percent": 48.1
+      }
+    }
+  },
+  "verification_scope": "Offline equality to accepted flags, hashes and states; raw predictions unavailable; not a fresh native audit or official scorer parity check.",
+  "usage": {
+    "sealed_model_calls": 1000,
+    "unknown_usage_calls": 0,
+    "unsealed_episodes_excluded": 0,
+    "invalid_evidence_episodes_excluded": 0,
+    "known_token_subtotal": {
+      "input_tokens": 448041,
+      "output_tokens": 6100871,
+      "total_tokens": 6548912
+    },
+    "unknown_by_field": {
+      "input_tokens": 0,
+      "output_tokens": 0,
+      "total_tokens": 0
+    },
+    "total_tokens_complete": true,
+    "usd": null,
+    "usd_status": "unknown_no_verified_price_or_billing_receipt",
+    "summed_episode_seconds": 123626.58500000021
+  }
+}

results/qwen3.7-max/deepagents/README.md

@@ -0,0 +1,11 @@
+# Qwen3.7-Max / deepagents
+
+固定 1,000 题：成功 519、确定失败 474、任务 unknown 6、invalid evidence 1。已封存 999 条；无待开始或在途记录。原生完整复现率 24.8%。
+
+`results.jsonl` 与 `results.csv` 保存逐题状态、指标、用量和结果哈希；`summary.json` 分别保存本地 HF 四维和 local-paper-v1 五维；`config.json` 保存任务清单、协议、源代码版本和接续来源。上一级含配对表、来源与导出核验。
+
+`resolved` 仅表示有效封存，`definite_outcome` 表示成功或确定失败。任务 unknown、无效证据与指标 null 分开保留，均不从 1,000 的分母移除。无效记录仅有 `unverified_result_sha256`，不可当作有效执行结果。后续阶段 pending 可能表示前序失败后没有执行到，不表示任务仍待派发。
+
+原始预测三元组不在源评分快照中，prediction 字段为空，并有明确导出状态；不能据此认为所有模型都没有生成预测。配对比较含历史协议修订，非严格等预算因果实验。本地评分尚未核实官方一致性。
+
+本次仅归档已接受的评分和状态，没有重新执行模型或程序。不包含 benchmark 输入、隐藏答案、原始提示词/API 轨迹、凭据或机器路径。

results/qwen3.7-max/deepagents/config.json

@@ -0,0 +1,1199 @@
+{
+  "schema_version": 2,
+  "model": "qwen3.7-max",
+  "arm": "deepagents",
+  "harness": "DeepAgents 0.7.13",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "dataset": {
+    "repo_id": "CamoAiLab/InferenceNet",
+    "revision": "59f9512a38e594528807744214a60ee00367434e",
+    "task_directory": "Selected_1000",
+    "task_list": "Selected_1000/1000_new.csv",
+    "prior_results_imported": false,
+    "engineering_pilot": false,
+    "expected_tasks": 1000,
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+    "Unknown and invalid evidence remain in the denominator; no replacement or rescoring.",
+    "Invalid evidence is not sealed; its unverified hash is distinct from a verified result hash."
+  ]
+}

results/qwen3.7-max/deepagents/summary.json

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+}

results/qwen3.7-max/diagnostics.json

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+      },
+      {
+        "generation": "uncertain",
+        "execution": "pending",
+        "scoring": "pending",
+        "count": 6
+      },
+      {
+        "generation": null,
+        "execution": null,
+        "scoring": null,
+        "count": 1
+      }
+    ]
+  },
+  "task_unknown_ids": {
+    "baseline": [],
+    "deepagents": [
+      86,
+      440,
+      597,
+      609,
+      718,
+      882
+    ]
+  },
+  "invalid_evidence_ids": {
+    "baseline": [],
+    "deepagents": [
+      453
+    ]
+  },
+  "raw_error_reasons_verified": false
+}

results/qwen3.7-max/export-verification.json

@@ -0,0 +1,44 @@
+{
+  "status": "passed_offline",
+  "per_arm": {
+    "baseline": {
+      "records": 1000,
+      "unique_task_ids": 1000,
+      "counts": {
+        "succeeded": 483,
+        "failed": 517,
+        "unknown": 0,
+        "unsealed": 0,
+        "not_started": 0,
+        "invalid_evidence": 0,
+        "completed": 1000,
+        "planned": 1000
+      },
+      "sealed_count": 1000,
+      "all_slots_sealed": true,
+      "metrics_recomputed": 9,
+      "matches_accepted_flags_states_hashes": true
+    },
+    "deepagents": {
+      "records": 1000,
+      "unique_task_ids": 1000,
+      "counts": {
+        "succeeded": 519,
+        "failed": 474,
+        "unknown": 6,
+        "unsealed": 0,
+        "not_started": 0,
+        "invalid_evidence": 1,
+        "completed": 993,
+        "planned": 1000
+      },
+      "sealed_count": 999,
+      "all_slots_sealed": false,
+      "metrics_recomputed": 9,
+      "matches_accepted_flags_states_hashes": true
+    }
+  },
+  "paired_rows": 1000,
+  "metrics_recomputed": 18,
+  "official_parity_verified": false
+}

results/qwen3.7-max/provenance.json

@@ -0,0 +1,24 @@
+{
+  "model": "qwen3.7-max",
+  "archived_at_utc": "2026-09-16T17:18:47.373930+00:00",
+  "result_snapshot_sha256": "eff050fe7977423fdffc731fc62b9ea45652743d2f3184931ae70c3b9365d176",
+  "accepted_results_sha256": "dd72f352be1895b11914dd2aea1fdceb21c453932877c588ecaf81ec09861105",
+  "accepted_task_records_sha256": "32a797b4da8dfe90d44b37d7715fe726a29c5b4f93a1b24d7d5ffbffb81e9749",
+  "record_count": 2000,
+  "selected_task_count": 1000,
+  "source_commits": [
+    "4afeaefac6183dc7111c7c02a056c9bf1e40b462",
+    "9d6a89eb6c4e42fab8c14b768d1bc4e40f15f980"
+  ],
+  "historical_native_audit": {
+    "mode": "fresh_in_accepted_snapshot",
+    "collection_interval": {
+      "started_at": "2026-09-16T06:46:01.177744+00:00",
+      "finished_at": "2026-09-16T07:43:33.877909+00:00"
+    }
+  },
+  "official_parity_verified": false,
+  "new_model_calls": 0,
+  "new_benchmark_executions": 0,
+  "verification_scope": "Offline equality and metric reaggregation of accepted score exports. No fresh input/native audit; no raw prediction rescoring."
+}

results/verify_qwen_deepseek.py

@@ -0,0 +1,71 @@
+"""Offline validation for the four added Qwen/DeepSeek result groups."""
+import csv
+import hashlib
+import json
+from collections import Counter
+from pathlib import Path
+
+root=Path(__file__).resolve().parent
+for line in (root/'manifest.sha256').read_text().splitlines():
+    expected,name=line.split('  ',1)
+    p=(root/name).resolve()
+    assert p.is_relative_to(root) and p.is_file(),name
+    assert hashlib.sha256(p.read_bytes()).hexdigest()==expected,name
+rows_by_model={}
+checked=0
+for model in ('qwen3.7-max','deepseek-v4-pro'):
+    rows_by_model[model]={}
+    for arm in ('baseline','deepagents'):
+        p=root/model/arm
+        rows=[json.loads(line) for line in (p/'results.jsonl').read_text().splitlines()]
+        config=json.loads((p/'config.json').read_text())
+        summary=json.loads((p/'summary.json').read_text())
+        assert len(rows)==1000 and len({r['task_id'] for r in rows})==1000
+        assert [r['task_id'] for r in rows]==config['dataset']['task_ids']
+        assert all(r['model']==model and r['arm']==arm for r in rows)
+        assert all(r['resolved']==(r['state']!='invalid_evidence') and r['definite_outcome']==(r['state'] in ('succeeded','failed')) for r in rows)
+        assert all(r['prediction_export_status']==('invalid_evidence_quarantined' if r['state']=='invalid_evidence' else 'not_available_in_accepted_score_snapshot') for r in rows)
+        assert all(r[k] is None for r in rows for k in ('prediction_coefficient','prediction_standard_error','prediction_p_value'))
+        with (p/'results.csv').open() as f:csv_rows=list(csv.DictReader(f))
+        assert len(csv_rows)==1000
+        for j,c in zip(rows,csv_rows):
+            assert set(j)==set(c)
+            assert all(c[k]==('' if v is None else str(v)) for k,v in j.items())
+        assert summary['official_parity_verified'] is False and summary['included_in_displayed_leaderboard'] is False
+        counts=summary['result']['task_counts']
+        assert Counter(r['state'] for r in rows)=={k:counts[k] for k in ('succeeded','failed','unknown','invalid_evidence') if counts[k]}
+        assert sum(r['state']=='unknown' for r in rows)==summary['result']['task_unknown_count']
+        assert summary['result']['invalid_evidence_count']==sum(r['state']=='invalid_evidence' for r in rows)
+        assert summary['result']['sealed_count']==sum(r['resolved'] for r in rows)
+        assert summary['all_slots_sealed']==all(r['resolved'] for r in rows)
+        for r in rows:
+            if r['state']=='invalid_evidence':
+                assert r['selected_result_sha256'] is None and r['unverified_result_sha256']
+                assert all(r[k] is None for k in r if k.startswith('local_') or k in summary['result']['metrics'])
+        for metrics,prefix in [(summary['result']['metrics'],''),(summary['legacy_local_paper']['metrics'],'local_')]:
+            for name,m in metrics.items():
+                flags=[r[prefix+name] for r in rows]
+                assert all(v is None or type(v) is bool for v in flags)
+                good,bad,unknown=sum(v is True for v in flags),sum(v is False for v in flags),sum(v is None for v in flags)
+                assert (m['count'],m['failure_count'],m['unknown_count'],m['denominator'])==(good,bad,unknown,1000)
+                assert m['score']==round(good/10,1) and m['rate']==good/1000
+                assert m['assessable']==good+bad and m['coverage_percent']==round((good+bad)/10,1)
+                checked+=1
+        rows_by_model[model][arm]=rows
+    b,d=rows_by_model[model]['baseline'],rows_by_model[model]['deepagents']
+    assert [r['task_id'] for r in b]==[r['task_id'] for r in d]
+    with (root/model/'paired_comparison.csv').open() as f:pairs=list(csv.DictReader(f))
+    assert len(pairs)==1000
+    for i,pair in enumerate(pairs):
+        assert int(pair['task_id'])==b[i]['task_id']
+        for arm in ('baseline','deepagents'):
+            r=rows_by_model[model][arm][i]
+            assert pair[arm+'_result_sha256']==(r['selected_result_sha256'] or '')
+            assert pair[arm+'_unverified_result_sha256']==(r['unverified_result_sha256'] or '')
+            assert pair[arm+'_state']==r['state']
+            for field,value in r.items():
+                key=arm+'_'+field if field.startswith('local_') else arm+'_hf_'+field
+                if key in pair:assert pair[key]==('' if value is None else str(value))
+assert checked==36
+print('PASS: archive manifest; 4 x 1000 unique task records; paired rows; 36 metric aggregates; unknowns and invalid evidence retained.')
+print('Offline export verification only; not fresh raw prediction scoring or official scorer parity.')