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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Built a matched directed recurrent dynamics model with positive softplus edge gates and a normalized Laplacian-gap penalty, plus a numerical collision/discriminant sanity check. The eight-seed benchmark found baseline MSE 0.00808 versus idea MSE 0.00918, paired delta +0.00110 and permutation p=0.30765; therefore there was no significant task-metric improvement. The trained-model mechanism signature was not confirmed because the implementation incorrectly discarded complex/nonzero eigenvalues, producing gap=0 for all models.", "metrics": { "baseline": "dynamics directed_rnn_laplacian, best lr=0.006: mean test MSE 0.0080788132, std 0.0022047114", "idea": "gmin=0.01, beta=20, best lr=0.006: mean test MSE 0.0091805133, std 0.0043079289", "paired_delta": "idea - baseline = +0.0011017001; idea wins 3/8; permutation p=0.30765", "math_check": "gap log slope 1.0, discriminant log slope 2.0, exact collision defective=true" }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "directed_rnn_laplacian", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.006 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.1310226163 }, { "cfg": { "lr": 0.003 }, "mean": 0.0194599919 }, { "cfg": { "lr": 0.006 }, "mean": 0.0092220744 } ], "full": { "mean": 0.0080788132, "std": 0.0022047114, "per_seed": [ 0.0094642192, 0.0093405331, 0.0054481933, 0.0126353521, 0.0079713278, 0.007394182, 0.0060087088, 0.0063679894 ], "n": 8 } }, "idea": { "mean": 0.0091805133, "std": 0.0043079289, "per_seed": [ 0.0121637192, 0.0096761212, 0.0077557201, 0.0169993993, 0.012369886, 0.0070991646, 0.0028650258, 0.00451507 ], "n": 8, "best_cfg": { "lr": 0.006, "gmin": 0.01, "beta": 20.0 }, "trials": [ { "cfg": { "lr": 0.001, "gmin": 0.01, "beta": 20.0 }, "mean": 0.271285017 }, { "cfg": { "lr": 0.003, "gmin": 0.01, "beta": 20.0 }, "mean": 0.0183764222 }, { "cfg": { "lr": 0.006, "gmin": 0.01, "beta": 20.0 }, "mean": 0.0091805133 } ] }, "comparison": { "delta_mean": 0.0011017001, "idea_wins": 3, "n_pairs": 8, "per_seed_diffs": [ 0.0026994999, 0.0003355881, 0.0023075268, 0.0043640472, 0.0043985583, -0.0002950174, -0.0031436831, -0.0018529193 ], "p_value": 0.30765, "mde": 0.0023397362, "mde_rel_pct": 28.9614, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "prediction": "smaller normalized spectral gap predicts larger eigenvector conditioning", "baseline_mean_gap": 0.0, "idea_mean_gap": 0.0, "baseline_mean_condition": 27.6053821, "idea_mean_condition": 14.2276043, "confirmed": false } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py", "files": [ "bench_experiment.py", "results.json", "run.log" ], "limitations": "Only the built-in dynamics track was tested; no vision, sequence, tabular, Cora, long-horizon rollout stability, condition-number penalty, or corrected complex-spectrum gap implementation was tested. The current signature computation filters eigenvalues by positive real part and therefore cannot validate the intended normalized nonzero gap for directed matrices with complex eigenvalues.", "system_verdict": "failed", "practical_verdict": "inconclusive", "mechanism_ok": 0, "system_judged": true }