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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Implemented excitation-gated recurrent training on the structurally matched dynamics track using the shared rnn_small architecture and a Jacobian smallest-singular-value gate. The mechanism signature was confirmed: low-excitation windows had higher trained-model residual MSE (0.001299 vs 0.000594), but the best gated model was worse than the tuned baseline (MSE 0.000751 vs 0.000687), with paired delta +0.0000644 and permutation p=0.2782. Therefore there was no significant task-metric win.", "metrics": { "baseline": "Tuned lr=0.01; full 8-seed mean MSE 0.000686979, std 0.000196252.", "idea": "Best lr=0.01; full 8-seed mean MSE 0.000751409, std 0.000237290; paired delta +0.0000644303, 4/8 wins, p=0.2782.", "mechanism_signature": "q25 sigma=0.0773184, q75 sigma=0.1157134; low-excitation train MSE=0.00129865, high-excitation train MSE=0.000593553; confirmed=true" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json" ], "limitations": "Only the built-in dynamics pendulum track was tested. No multimodal sensor-fusion or learned explicit (p,x,psi) calibration head was evaluated; the gate used a precomputed analytic Jacobian score from observed trajectory states. Only 15 epochs, 400 training samples, one threshold, and one gate floor were tested.", "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.0061489524 }, { "cfg": { "lr": 0.003 }, "mean": 0.0013683813 }, { "cfg": { "lr": 0.01 }, "mean": 0.0007866572 } ], "full": { "mean": 0.0006869792, "std": 0.0001962519, "per_seed": [ 0.0008465874, 0.0005530674, 0.0006530179, 0.0010939559, 0.0006159734, 0.000391073, 0.0006219872, 0.000720171 ], "n": 8 } }, "idea": { "best_cfg": { "lr": 0.01 }, "mean": 0.0007514095, "std": 0.0002372905, "per_seed": [ 0.001134159, 0.0006296231, 0.0008904426, 0.001055335, 0.0005659242, 0.0003978782, 0.0006218505, 0.000716063 ], "n": 8 }, "comparison": { "delta_mean": 6.44303e-05, "idea_wins": 4, "n_pairs": 8, "p_value": 0.2782, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "low_q25_sigma": 0.0773184, "high_q75_sigma": 0.1157134, "low_excitation_train_mse": 0.00129865, "high_excitation_train_mse": 0.000593553, "confirmed": true }, "idea_sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.005116059 }, { "cfg": { "lr": 0.003 }, "mean": 0.0013088752 }, { "cfg": { "lr": 0.01 }, "mean": 0.0007514095 } ], "method": { "tau": 0.2, "floor": 0.15, "epochs": 15, "batch": 128 }, "protocol_notes": "Matched dynamics track; baseline and idea shared rnn_small, Adam, epochs, batch, data, and the union learning-rate grid." }, "system_verdict": "partial", "practical_verdict": "inconclusive", "mechanism_ok": 1, "system_judged": true }