Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Built and evaluated distributed e-value prediction sets on the registered vision/cnn_small benchmark with held-out local calibration, entropy-attenuated convex fusion, an equal-budget baseline sweep, and 8 paired seeds. The mechanism signature was quantitatively confirmed, but the idea had slightly higher classification error than the tuned baseline and no significant improvement; its alpha=0.1 prediction sets were vacuous.", "metrics": { "baseline": "Test error mean 0.88375 across 8 seeds; sweep means lr=0.001: 0.88000, lr=0.003: 0.88625, lr=0.01: 0.89500.", "idea": "Test error mean 0.884375 across 8 seeds at lr=0.001; paired delta +0.000625, permutation p-value 0.7525, 1/8 paired wins; coverage 1.0 and average set size 10.0." }, "bench_report": { "bench_version": 1, "track": "vision", "model": "cnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.001 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.88 }, { "cfg": { "lr": 0.003 }, "mean": 0.88625 }, { "cfg": { "lr": 0.01 }, "mean": 0.895 } ], "full": { "mean": 0.88375, "std": 0.025829972899714785, "per_seed": [ 0.9075, 0.885, 0.9075, 0.82, 0.8875, 0.89, 0.8925, 0.88 ], "n": 8 } }, "idea": { "mean": 0.884375, "std": 0.02533371024938904, "per_seed": [ 0.9075, 0.8825, 0.9075, 0.8225, 0.8875, 0.89, 0.8975, 0.88 ], "n": 8 }, "comparison": { "delta_mean": 0.0006250000000000006, "idea_wins": 1, "n_pairs": 8, "per_seed_diffs": [ 0.0, -0.0025000000000000577, 0.0, 0.0025000000000000577, 0.0, 0.0, 0.0050000000000000044, 0.0 ], "p_value": 0.7525, "mde": 0.0018529277478734423, "mde_rel_pct": 0.20966650612429333, "verdict": "no measurable effect", "system_worked": false }, "mechanism_signature": { "prediction": "fused mean e-value equals uncertainty-weighted mean local e-values", "confirmed": true, "max_abs_error": 2.1523280469004646e-07 }, "idea_sweep": [ { "lr": 0.001, "result": { "mean": 0.88, "std": 0.0347311099736245, "per_seed": [ 0.9075, 0.8825, 0.9075, 0.8225 ], "n": 4 } }, { "lr": 0.003, "result": { "mean": 0.881875, "std": 0.04258722666481113, "per_seed": [ 0.9, 0.9275, 0.8875, 0.8125 ], "n": 4 } }, { "lr": 0.01, "result": { "mean": 0.895, "std": 0.012119199643540817, "per_seed": [ 0.9, 0.9075, 0.875, 0.8975 ], "n": 4 } } ] }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py", "files": [ "bench_experiment.py", "bench_report.json" ], "limitations": "The compact run used 400 training and 400 test CIFAR examples, 3 epochs, and two experts. Uncertainty was mean calibration entropy rather than a separately calibrated uncertainty model; formal finite-sample validity under adaptive weights and distribution shift was not tested; prediction sets were vacuous at alpha=0.1.", "system_verdict": "partial", "practical_verdict": "no_effect", "mechanism_ok": 1, "system_judged": true }