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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "The PITO recurrent-gain system was evaluated against the same positive recurrent architecture with a fixed gain on the registered dynamics/control track. The tuned baseline reached mean MSE 0.0003413614 versus 0.0003760458 for the idea; paired delta was +0.0000346845 with permutation p=0.41415, so there was no significant win. The trained-model mechanism signature was not confirmed.", "metrics": { "baseline": "Best config lr=0.01, gain=1.5; full 8-seed mean MSE 0.00034136135218432173.", "idea": "Best config lr=0.01, a=1.0, b=0.2, initial gain=1.0; full 8-seed mean MSE 0.00037604584758810233.", "comparison": "delta_mean=0.0000346844954037806, idea_wins=1/8, p_value=0.41415, verdict=no significant win." }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "positive_rnn_fixed_gain_vs_pito", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01, "gain": 1.5 }, "sweep": [ { "cfg": { "lr": 0.001, "gain": 0.5 }, "mean": 0.007410152786178514 }, { "cfg": { "lr": 0.001, "gain": 1.0 }, "mean": 0.004754966095788404 }, { "cfg": { "lr": 0.001, "gain": 1.5 }, "mean": 0.0033777739736251533 }, { "cfg": { "lr": 0.003, "gain": 0.5 }, "mean": 0.00141466197965201 }, { "cfg": { "lr": 0.003, "gain": 1.0 }, "mean": 0.001106211231672205 }, { "cfg": { "lr": 0.003, "gain": 1.5 }, "mean": 0.0007843969069654122 }, { "cfg": { "lr": 0.01, "gain": 0.5 }, "mean": 0.0005034581408835948 }, { "cfg": { "lr": 0.01, "gain": 1.0 }, "mean": 0.0003801305138040334 }, { "cfg": { "lr": 0.01, "gain": 1.5 }, "mean": 0.00034718124516075477 } ], "full": { "mean": 0.00034136135218432173, "std": 0.00014732674795547322, "per_seed": [ 0.00023207295453175902, 0.00027615175349637866, 0.0003660226066131145, 0.0005144776660017669, 0.000629094778560102, 0.00019970460562035441, 0.00032621651189401746, 0.0001871499407570809 ], "n": 8 } }, "idea": { "mean": 0.00037604584758810233, "std": 9.077411347953533e-05, "per_seed": [ 0.00023790601699147373, 0.0003053620457649231, 0.0004130469460505992, 0.0005384435644373298, 0.00042402392136864364, 0.00027976761339232326, 0.0004256583342794329, 0.00038415833842009306 ], "n": 8 }, "comparison": { "delta_mean": 3.46844954037806e-05, "idea_wins": 1, "n_pairs": 8, "per_seed_diffs": [ 5.833062459714711e-06, 2.9210292268544436e-05, 4.702433943748474e-05, 2.396589843556285e-05, -0.00020507085719145834, 8.006300777196884e-05, 9.944182238541543e-05, 0.00019700839766301215 ], "p_value": 0.41415, "mde": 9.544819469810646e-05, "mde_rel_pct": 27.96104306692814, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "prediction": { "prediction": "decay slope = aV when y>=V", "predicted_rate": null, "observed_rate": null, "relative_error": null, "n_traces": 0, "confirmed": false }, "selected_idea_cfg": { "lr": 0.01, "a": 1.0, "b": 0.2, "gain": 1.0 }, "matched_structure": "dynamics/control" }, "idea_sweep": [ { "cfg": { "lr": 0.01, "a": 1.0, "b": 0.2, "gain": 1.0 }, "result": { "mean": 0.00037604584758810233, "std": 9.077411347953533e-05, "per_seed": [ 0.00023790601699147373, 0.0003053620457649231, 0.0004130469460505992, 0.0005384435644373298, 0.00042402392136864364, 0.00027976761339232326, 0.0004256583342794329, 0.00038415833842009306 ], "n": 8 }, "mechanism_signature": { "prediction": "decay slope = aV when y>=V", "predicted_rate": null, "observed_rate": null, "relative_error": null, "n_traces": 0, "confirmed": false } }, { "cfg": { "lr": 0.001, "a": 1.0, "b": 0.2, "gain": 1.0 }, "result": { "mean": 0.004910496441880241, "std": 0.0021499903596063027, "per_seed": [ 0.004891040734946728, 0.002062235027551651, 0.006821547634899616, 0.008928792551159859, 0.005618015769869089, 0.0028769611380994324, 0.0052522034384310246, 0.002833175240084529 ], "n": 8 }, "mechanism_signature": { "prediction": "decay slope = aV when y>=V", "predicted_rate": 0.21370937302708626, "observed_rate": 0.000306834834250262, "relative_error": 0.9985642425041817, "threshold_V": 0.21370937302708626, "n_traces": 2, "confirmed": false } }, { "cfg": { "lr": 0.01, "a": 1.0, "b": 0.2, "gain": 1.0 }, "result": { "mean": 0.00037604584758810233, "std": 9.077411347953533e-05, "per_seed": [ 0.00023790601699147373, 0.0003053620457649231, 0.0004130469460505992, 0.0005384435644373298, 0.00042402392136864364, 0.00027976761339232326, 0.0004256583342794329, 0.00038415833842009306 ], "n": 8 }, "mechanism_signature": { "prediction": "decay slope = aV when y>=V", "predicted_rate": null, "observed_rate": null, "relative_error": null, "n_traces": 0, "confirmed": false } } ], "custom_track": null }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json", "stage2_output.txt" ], "limitations": "Only the registered built-in dynamics track was tested. No other tracks were structurally matched to the stability/control idea. The selected trained-model run did not yield enough valid high-output decay traces for quantitative signature confirmation; the lower-learning-rate exploratory setting produced a relative signature error of approximately 99.86%.", "system_verdict": "failed", "practical_verdict": "inconclusive", "mechanism_ok": 0, "system_judged": true }