| 1 |
Re-run analysis.py from clean state (results.json deleted) → byte-identical results.json |
PASS (cmp identical) |
| 2 |
n_supported + n_not_supported + n_not_assessable = 6 = n_analysed |
PASS (2+3+1=6) |
| 3 |
exclusions: n_raw 6 − removed 0 = n_analysed 6 |
PASS |
| 4 |
Every verdict has one locator and one reason; locators follow the TASK format |
PASS |
| 5 |
Extract SHA-256 equal to README values |
PASS |
| 6 |
A1: 100(exp(-0.431)-1) = -35.01% matches printed -35.0%; |
z |
| 7 |
A3: 100(exp(-0.283)-1) = -24.65% (printed -24.7%) ≠ -28.3% |
PASS (verdict not_supported) |
| 8 |
A4: CI95 = [-0.896, 0.084] (1.96) / [-0.906, 0.094] (2.0); contains estimate; includes 0; asserted interval = b ± 1·SE |
PASS (verdict not_supported) |
| 9 |
A5: regex search for men/women/male/female/sex/gender in DCR extract returns no lines |
PASS (not_assessable) |
| 10 |
A6: -1.99/17.3 = -11.50%; CI in Table 2 = [-2.24, -1.75] |
PASS |
| 11 |
Baseline vs final: A3/A4 have only 75% of numbers found verbatim, both judged not_supported; A2 has 100% numeric match yet fails on sign — illustrates why verbatim match is insufficient |
consistent |
| 12 |
random_seed null (no randomness) |
PASS |