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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Built a local multichannel amplitude-coupling sequence track and matched end-to-end temporal CNN systems, with fixed Morlet cross-channel scattering as the only intervention. The math sanity check passed to approximately 1.2e-7 error and the implementation signature matched exactly, but SNST test error was 0.48750 versus 0.48312 for the tuned raw baseline (paired delta +0.00438, p=0.64655), so there is no observed transfer win.", "metrics": { "baseline": "8-seed test error mean 0.483125, std 0.031319; per-seed [0.4850, 0.4850, 0.4950, 0.4850, 0.5000, 0.5400, 0.4400, 0.4350]; best sweep lr=0.006, weight_decay=0.001, epochs=18", "idea": "8-seed test error mean 0.487500, std 0.018708; per-seed [0.4750, 0.5000, 0.4800, 0.5000, 0.5000, 0.5000, 0.5000, 0.4450]; best idea setting lr=0.006, weight_decay=0.001, epochs=18", "paired_comparison": "idea minus baseline = +0.004375 mean; 3/8 idea wins; permutation p=0.64655; verdict no measurable effect" }, "bench_report": { "bench_version": 1, "track": "multichannel_amplitude_coupling", "model": "matched_temporal_cnn", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.006, "epochs": 18, "weight_decay": 0.001 }, "sweep": [ { "cfg": { "lr": 0.001, "epochs": 18, "weight_decay": 0.0 }, "mean": 0.49875 }, { "cfg": { "lr": 0.001, "epochs": 18, "weight_decay": 0.001 }, "mean": 0.49125 }, { "cfg": { "lr": 0.003, "epochs": 18, "weight_decay": 0.0 }, "mean": 0.48875 }, { "cfg": { "lr": 0.003, "epochs": 18, "weight_decay": 0.001 }, "mean": 0.48875 }, { "cfg": { "lr": 0.006, "epochs": 18, "weight_decay": 0.0 }, "mean": 0.48875 }, { "cfg": { "lr": 0.006, "epochs": 18, "weight_decay": 0.001 }, "mean": 0.4875 } ], "full": { "mean": 0.483125, "std": 0.031319, "per_seed": [ 0.485, 0.485, 0.495, 0.485, 0.5, 0.54, 0.44, 0.435 ], "n": 8 } }, "idea": { "mean": 0.4875, "std": 0.018708, "per_seed": [ 0.475, 0.5, 0.48, 0.5, 0.5, 0.5, 0.5, 0.445 ], "n": 8 }, "comparison": { "delta_mean": 0.004375, "idea_wins": 3, "n_pairs": 8, "per_seed_diffs": [ -0.01, 0.015, -0.015, 0.015, 0.0, -0.04, 0.06, 0.01 ], "p_value": 0.64655, "mde": 0.02432, "mde_rel_pct": 5.03393, "verdict": "no measurable effect", "system_worked": false }, "mechanism_signature": { "quantity": "mean first-edge first-band SNST output measured on the trained idea system versus an independent direct recomputation", "predicted": 13.9836053848, "observed": 13.9836053848, "relative_error": 0.0, "confirmed": true }, "math_check": { "identity_max_error": 1.1920929e-07, "phase_invariance_max_error": 1.1920929e-07, "passed": true }, "custom_track": { "name": "multichannel_amplitude_coupling", "file": "bench_experiment.py", "domain": "sequence" }, "idea_sweep": [ { "cfg": { "lr": 0.006, "epochs": 18, "weight_decay": 0.001 }, "mean": 0.4875 }, { "cfg": { "lr": 0.001, "epochs": 18, "weight_decay": 0.0 }, "mean": 0.48875 }, { "cfg": { "lr": 0.006, "epochs": 18, "weight_decay": 0.0 }, "mean": 0.490625 } ] }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py", "files": [ "bench_experiment.py", "bench_report.json", "bench_run.log" ], "limitations": "This is a deterministic synthetic multichannel sequence track rather than real EEG or BCI Competition IV-2a. The SNST front end is fixed rather than learned, only three local edges and two bands were tested, and parameter/FLOP equality was not formally counted. The mechanism signature verifies trained-model implementation consistency, not that coupling improves prediction; no channelwise-scattering ablation or real-subject evaluation was run.", "system_verdict": "partial", "practical_verdict": "no_effect", "mechanism_ok": 1, "system_judged": true }