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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Gramian regularization was tested on the structurally matched registered dynamics track with rnn_small under identical task, architecture, and paired-seed budget. Baseline MSE was 0.0067402332 and idea MSE was 0.0067282456, but delta_mean=-0.0000119877 and permutation p=0.5437, so there was no significant win.", "metrics": { "baseline": "mean=0.0067402332, std=0.0039325375, best_cfg={lr:0.003, weight_decay:0.0001}", "idea": "mean=0.0067282456, std=0.0039155327, best_cfg={lr:0.003, weight_decay:0.0001, reg:0.1}, 4/8 paired wins" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_gramian_bench.py", "files": [ "stage2_gramian_bench.py", "bench_report.json", "bench_stdout.txt" ], "limitations": "The exact higher-order GRU Jacobian implementation exceeded the time budget, so the final run used a differentiable gate-matrix local-linearization proxy. Only the registered dynamics track was tested; the model-derived signature did not confirm simultaneous observability and reachability improvement.", "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.003, "weight_decay": 0.0001 }, "sweep": [ { "cfg": { "lr": 0.0015, "weight_decay": 0.0 }, "mean": 0.013899383 }, { "cfg": { "lr": 0.0015, "weight_decay": 0.0001 }, "mean": 0.0139304754 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0 }, "mean": 0.0062442472 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001 }, "mean": 0.0062287434 }, { "cfg": { "lr": 0.006, "weight_decay": 0.0 }, "mean": 0.0077281742 }, { "cfg": { "lr": 0.006, "weight_decay": 0.0001 }, "mean": 0.0077230021 } ], "full": { "mean": 0.0067402332, "std": 0.0039325375, "per_seed": [ 0.0058188373, 0.0031118754, 0.0123605821, 0.0036236786, 0.0028440626, 0.0046730894, 0.0078400327, 0.0136497077 ], "n": 8 } }, "idea": { "mean": 0.0067282456, "std": 0.0039155327, "per_seed": [ 0.0058188438, 0.003111881, 0.0122646708, 0.0036237042, 0.0028439818, 0.0046730391, 0.007840001, 0.0136498427 ], "n": 8, "best_cfg": { "lr": 0.003, "weight_decay": 0.0001, "reg": 0.1 }, "sweep": [ { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "reg": 0.01 }, "mean": 0.0067282543 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "reg": 0.03 }, "mean": 0.0067282481 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "reg": 0.1 }, "mean": 0.0067282456 } ] }, "comparison": { "delta_mean": -1.19877e-05, "idea_wins": 4, "n_pairs": 8, "p_value": 0.5437, "verdict": "no measurable effect", "system_worked": false }, "mechanism_signature": { "baseline_normalized_observability": -1.5687e-06, "idea_normalized_observability": -1.7482e-06, "baseline_normalized_reachability": -1.4856e-06, "idea_normalized_reachability": -1.11e-06, "predicted": "regularization increases both normalized minimum Gramian eigenvalues", "confirmed": false } }, "system_verdict": "failed", "practical_verdict": "no_effect", "mechanism_ok": 0, "system_judged": true }