| |
| """verify.py — read every condensed table and print/assert each paper claim. |
| |
| Run from the reviewer-pack root: |
| |
| python verify.py |
| |
| Exits with code 0 if all assertions pass (within a 2e-3 tolerance on |
| coefficient values), prints any mismatches otherwise. |
| """ |
| from __future__ import annotations |
|
|
| import sys |
| from pathlib import Path |
|
|
| import pandas as pd |
|
|
| ROOT = Path(__file__).resolve().parent |
| TABLES = ROOT / "tables" |
|
|
| TOL = 2e-3 |
|
|
| def banner(s: str) -> None: |
| print(f"\n{'═' * 78}\n {s}\n{'═' * 78}") |
|
|
| def claim(desc: str, actual: float, expected: float, tol: float = TOL) -> bool: |
| ok = abs(actual - expected) <= tol |
| tick = "PASS" if ok else "FAIL" |
| print(f" [{tick}] {desc}\n actual={actual:.4f} expected={expected:.4f} diff={abs(actual-expected):.4f}") |
| return ok |
|
|
|
|
| def main() -> int: |
| fails = 0 |
|
|
| |
| banner("Table 2 — DML Spec B headline (mutually-controlled, 6 treatments)") |
| t2 = pd.read_csv(TABLES / "table2_dml_headline.csv") |
| print(t2.to_string(index=False)) |
|
|
| |
| def lookup(outcome: str, t_pretty: str) -> float: |
| sub = t2[(t2.outcome == outcome) & (t2.treatment == t_pretty)] |
| return float(sub.iloc[0]["coef"]) |
|
|
| banner("DML claim checks") |
| fails += not claim("T5 topical comp. selected", lookup("selected","T5 topical competence"), +0.037, tol=0.005) |
| fails += not claim("T2a Q-headings selected", lookup("selected","T2a Q-headings"), +0.016, tol=0.005) |
| fails += not claim("T3 schema selected", lookup("selected","T3 schema (JSON-LD)"), -0.014, tol=0.005) |
| fails += not claim("T6 freshness selected", lookup("selected","T6 freshness"), -0.005, tol=0.005) |
| fails += not claim("T5 topical comp. rank_delta", lookup("rank_delta","T5 topical competence"), -0.530, tol=0.02) |
| fails += not claim("T2a Q-headings rank_delta", lookup("rank_delta","T2a Q-headings"), +0.136, tol=0.02) |
| fails += not claim("T3 schema post_rank", lookup("post_rank","T3 schema (JSON-LD)"), +0.095, tol=0.01) |
|
|
| |
| banner("Admission probe — pre-commitment headline (mean pooling)") |
| adm = pd.read_csv(TABLES / "admission_probe_headline.csv") |
| pooled = adm[adm.pooling == "mean"].mean(numeric_only=True) |
| print(adm[adm.pooling == "mean"].round(4).to_string(index=False)) |
|
|
| banner("Admission probe claim checks (variant-averaged)") |
| fails += not claim("Layer 0 ROC AUC", pooled["layer_0"], 0.671, tol=0.02) |
| fails += not claim("Peak ROC AUC", pooled["auc_peak"], 0.860, tol=0.02) |
| fails += not claim("L0 → peak gain", pooled["delta_L0_to_peak"], 0.190, tol=0.03) |
|
|
| |
| banner("Saliency — Llama vs Qwen on 4 treatments") |
| sal = pd.read_csv(TABLES / "saliency_summary.csv") |
| print(sal.to_string(index=False)) |
|
|
| banner("Saliency claim checks") |
| def sal_ratio(model: str, t: str) -> float: |
| return float(sal[(sal.model == model) & (sal.treatment == t)].iloc[0]["saliency_ratio"]) |
| fails += not claim("Qwen attends to T1b stats (>>1)", sal_ratio("Qwen-2.5-72B", "T1b_stats_density"), 1.93, tol=0.05) |
| fails += not claim("Llama ~baseline on T1b (<1)", sal_ratio("Llama-3.3-70B","T1b_stats_density"), 0.89, tol=0.05) |
| fails += not claim("Llama ignores T3 schema (<<1)", sal_ratio("Llama-3.3-70B","T3_structured_data_new"),0.19, tol=0.05) |
| fails += not claim("Qwen ignores T3 schema (<<1)", sal_ratio("Qwen-2.5-72B", "T3_structured_data_new"),0.40, tol=0.05) |
|
|
| |
| banner("Ablation — mean Δrank per (treatment, prompt) on full frame") |
| abl = pd.read_csv(TABLES / "ablation_summary.csv") |
| full_abl = abl[abl.frame == "full"] |
| print(full_abl.to_string(index=False)) |
|
|
| banner("Ablation claim checks") |
| def abl_mean(treatment, prompt) -> float: |
| sub = full_abl[(full_abl.treatment == treatment) & (full_abl.prompt == prompt)] |
| return float(sub.iloc[0]["mean_delta_r"]) |
| fails += not claim("T5 sign flip — biased (promotes URL)", abl_mean("T5_topical_comp","biased"), -0.167, tol=0.03) |
| fails += not claim("T5 sign flip — neutral (demotes URL)", abl_mean("T5_topical_comp","neutral"), +0.038, tol=0.03) |
|
|
| print() |
| print(f"{'═' * 78}") |
| if fails: |
| print(f" {fails} claim(s) FAILED — please inspect the printed values.") |
| return 1 |
| print(" All paper claims VERIFIED against the tables.") |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| sys.exit(main()) |
|
|
