| |
| """Validate the v1.1.0 SciBench tables against the campaign's reported numbers. |
| |
| Expected values are transcribed from the campaign's reported results (a |
| re-derivation from the frozen file), NOT recomputed here from prose. |
| |
| Where this validator disagrees with a reported value, the disagreement is listed |
| in the card's defects section rather than silently reconciled. |
| |
| Exits nonzero on any mismatch. |
| """ |
| import os, collections |
| import pandas as pd |
| from scipy import stats |
|
|
| ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) |
| D = os.path.join(ROOT, "data", "scibench") |
|
|
| tr = pd.read_parquet(os.path.join(D, "trajectories.parquet")) |
| ec = pd.read_parquet(os.path.join(D, "evaluator_calls.parquet")) |
| rm = pd.read_parquet(os.path.join(D, "role_messages.parquet")) |
|
|
| fails, checks = [], 0 |
|
|
|
|
| def chk(label, got, want, tol=5e-4): |
| global checks |
| checks += 1 |
| ok = (abs(got - want) <= tol) if isinstance(want, float) else (got == want) |
| if not ok: |
| fails.append(f"{label}: got {got!r}, expected {want!r}") |
| print(f" {'ok ' if ok else 'FAIL'} {label:<50} got={got!r:<20} want={want!r}") |
|
|
|
|
| print("[integrity]") |
| chk("trajectory rows", len(tr), 2296) |
| chk("trajectory_key unique", tr.trajectory_key.nunique(), 2296) |
| chk("distinct problems", tr.problem_uid.nunique(), 574) |
| chk("calls match submissions", int(tr.submissions.sum()), len(ec)) |
| chk("every call key in traj", int(ec.trajectory_key.isin(set(tr.trajectory_key)).all()), 1) |
| chk("every msg key in traj", int(rm.trajectory_key.isin(set(tr.trajectory_key)).all()), 1) |
| chk("one benchmark_id", tr.benchmark_id.nunique(), 1) |
| chk("benchmark_id value", tr.benchmark_id.iloc[0], "scibench") |
| chk("one domain", tr.domain.iloc[0], "science") |
| chk("no Arm C", int(tr.arm.isin(["A", "B"]).all()), 1) |
| chk("one config_version", tr.config_version.nunique(), 1) |
| chk("config_version value", tr.config_version.iloc[0], "aed89f28ab338bdb") |
|
|
| print("\n[census] all four cells exactly 574 (XDOMAIN-RESULTS 'Run quality')") |
| for a in ("gemma-4-31B-it", "gpt-oss-120b"): |
| for arm in ("A", "B"): |
| chk(f"cell {a}/{arm}", len(tr[(tr.actor_model == a) & (tr.arm == arm)]), 574) |
| chk("trajectory-level failures", int(tr.hard_failure.notna().sum()), 0) |
| chk("unjudged (no first verdict)", int((~tr.graded).sum()), 0) |
|
|
| print("\n[Q1] first-pass accuracy (XDOMAIN-RESULTS Q1)") |
| Q1 = {("gemma-4-31B-it", "A"): 0.794, ("gemma-4-31B-it", "B"): 0.794, |
| ("gpt-oss-120b", "A"): 0.784, ("gpt-oss-120b", "B"): 0.789} |
| for (a, arm), v in Q1.items(): |
| s = tr[(tr.actor_model == a) & (tr.arm == arm) & tr.graded] |
| chk(f"Q1 {a}/{arm} firstpass", round(float(s.first_pass_correct.mean()), 3), v) |
|
|
| print("\n[Q2] paired recovery on problems first-pass-wrong under BOTH arms") |
| Q2 = {"gemma-4-31B-it": (99, 0.2121, 0.0202, 21, 2, 6.6e-05), |
| "gpt-oss-120b": (96, 0.2188, 0.1354, 17, 9, 0.169)} |
| for a, (n_both, recA, recB, aonly, bonly, pexp) in Q2.items(): |
| s = tr[tr.actor_model == a] |
| w = s.pivot_table(index="problem_uid", columns="arm", |
| values=["first_pass_correct", "final_correct_prereg", "graded"], |
| aggfunc="first") |
| both = w[(w[("graded", "A")] == 1) & (w[("graded", "B")] == 1) |
| & (w[("first_pass_correct", "A")] == 0) & (w[("first_pass_correct", "B")] == 0)] |
| fa, fb = both[("final_correct_prereg", "A")], both[("final_correct_prereg", "B")] |
| ao = int(((fa == 1) & (fb == 0)).sum()); bo = int(((fb == 1) & (fa == 0)).sum()) |
| chk(f"Q2 {a} n_both", len(both), n_both) |
| chk(f"Q2 {a} recovery A", round(float(fa.mean()), 4), recA) |
| chk(f"Q2 {a} recovery B", round(float(fb.mean()), 4), recB) |
| chk(f"Q2 {a} A-only", ao, aonly) |
| chk(f"Q2 {a} B-only", bo, bonly) |
| p = stats.binomtest(bo, ao + bo, 0.5).pvalue |
| chk(f"Q2 {a} exact McNemar p", float(f"{p:.3g}"), pexp, tol=max(pexp * 0.02, 1e-7)) |
|
|
| print("\n[Q3] mechanism on first-pass-wrong (XDOMAIN-RESULTS Q3)") |
| Q3 = {("gemma-4-31B-it", "A"): (118, 5.36, 1.97, 0.042, 0.076), |
| ("gemma-4-31B-it", "B"): (118, 5.84, 5.84, 1.000, 0.932), |
| ("gpt-oss-120b", "A"): (124, 5.22, 2.69, 0.024, 0.008), |
| ("gpt-oss-120b", "B"): (121, 5.33, 5.20, 0.909, 0.355)} |
| for (a, arm), (n, cyc, sub, nref, frz) in Q3.items(): |
| w = tr[(tr.actor_model == a) & (tr.arm == arm) & tr.graded & (tr.first_pass_correct == 0)] |
| chk(f"Q3 {a}/{arm} n_fpw", len(w), n) |
| chk(f"Q3 {a}/{arm} cycles", round(float(w.cycles.mean()), 2), cyc, tol=6e-3) |
| chk(f"Q3 {a}/{arm} submissions", round(float(w.submissions.mean()), 2), sub, tol=6e-3) |
| chk(f"Q3 {a}/{arm} never_refuse", |
| round(float(w.reviewer_never_declines.dropna().mean()), 3), nref) |
| chk(f"Q3 {a}/{arm} frozen", round(float(w.frozen_answer.mean()), 3), frz) |
|
|
| print("\n[Q4] functional collapse (XDOMAIN-RESULTS Q4)") |
| Q4 = {("gemma-4-31B-it", "A"): 0.000, ("gemma-4-31B-it", "B"): 0.998, |
| ("gpt-oss-120b", "A"): 0.347, ("gpt-oss-120b", "B"): 0.990} |
| for (a, arm), v in Q4.items(): |
| s = tr[(tr.actor_model == a) & (tr.arm == arm)] |
| chk(f"Q4 collapse {a}/{arm}", round(float(s.functional_collapse.dropna().mean()), 3), v) |
|
|
| print("\n[noise floor] grader disagreement on byte-identical candidates") |
| sub = ec[ec.candidate_raw.notna() & ec.verdict.notna()] |
| g = sub.groupby(["problem_uid", "candidate_raw"]).verdict.agg(["nunique", "size"]) |
| multi = g[g["size"] >= 2]; disc = multi[multi["nunique"] > 1] |
| chk("noise: discordant groups", len(disc), 19) |
| chk("noise: multi-graded groups", len(multi), 678) |
| chk("noise floor (exact bytes)", round(len(disc) / len(multi), 4), 0.0280) |
|
|
| print("\n[F18] scoring defect, SciBench (re-derived; see card)") |
| F18 = {("gemma-4-31B-it", "A"): (0.288, 2), ("gemma-4-31B-it", "B"): (0.000, 0), |
| ("gpt-oss-120b", "A"): (0.105, 0), ("gpt-oss-120b", "B"): (0.017, 0)} |
| for (a, arm), (mr, uc) in F18.items(): |
| w = tr[(tr.actor_model == a) & (tr.arm == arm) & tr.graded & (tr.first_pass_correct == 0)] |
| chk(f"F18 {a}/{arm} mismatch", round(float(w.f18_mismatch.mean()), 3), mr) |
| chk(f"F18 {a}/{arm} undercredit", int(w.f18_under_credited.sum()), uc) |
| wfp = tr[tr.graded & (tr.first_pass_correct == 0)] |
| chk("F18 total mismatched (fpw)", int(wfp.f18_mismatch.sum()), 49) |
| chk("F18 total under-credited", int(wfp.f18_under_credited.sum()), 2) |
|
|
| print("\n" + "=" * 70) |
| if fails: |
| print(f"FAILED {len(fails)}/{checks}") |
| for f in fails: |
| print(" " + f) |
| raise SystemExit(1) |
| print(f"ALL {checks} CHECKS PASSED — SciBench tables reproduce the campaign") |
|
|
