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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Implemented exact global gradient projection versus the differentiable smooth radial surrogate in the structurally matched dynamics track using identical rnn_small systems, Adam settings, data, epochs, and paired seeds. The idea's best mean test MSE was 0.0010236 versus baseline 0.0012496, but the paired delta was -0.0002260 with permutation p=0.2949, hence no significant win. The trained-model signature did not confirm the predicted larger smooth applied norm: exact p95 was 0.0500000 while smooth p95 was 0.0499769.", "metrics": { "baseline": "best_cfg lr=0.003, radius=0.05; full 8-seed mean MSE=0.0012495772, std=0.0005645325", "idea": "best_cfg lr=0.006, radius=0.05; full 8-seed mean MSE=0.0010236013, std=0.0003525166; paired delta=-0.0002259759; p=0.2949; wins=5/8" }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.003, "radius": 0.05 }, "sweep": [ { "cfg": { "lr": 0.0015, "radius": 0.05 }, "mean": 0.0026964124 }, { "cfg": { "lr": 0.003, "radius": 0.05 }, "mean": 0.0010492465 }, { "cfg": { "lr": 0.006, "radius": 0.05 }, "mean": 0.0012117275 } ], "full": { "mean": 0.0012495772, "std": 0.0005645325, "per_seed": [ 0.0009961863, 0.0008429016, 0.0008552631, 0.0015026348, 0.0012220048, 0.0009713815, 0.0026426117, 0.0009636339 ], "n": 8 } }, "idea": { "best_cfg": { "lr": 0.006, "radius": 0.05 }, "mean": 0.0010236013, "std": 0.0003525166, "per_seed": [ 0.0007349217, 0.0010386385, 0.0008291155, 0.0018074878, 0.0007241229, 0.00072026, 0.0013001238, 0.0010341406 ], "n": 8 }, "comparison": { "delta_mean": -0.0002259759, "idea_wins": 5, "n_pairs": 8, "p_value": 0.2949, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "prediction": "smooth clipping can apply a different local gain and create larger gradients than exact projection near the boundary", "observed": { "cfg": { "lr": 0.006, "radius": 0.05 }, "baseline_grad_norm_p95": 1.7481883, "baseline_applied_norm_p95": 0.05, "idea_grad_norm_p95": 1.7462667, "idea_applied_norm_p95": 0.0499769, "idea_fraction_over_radius": 0.9791667 }, "confirmed": false }, "math_sanity": "Exact projection stayed bounded up to floating-point tolerance; smooth output remained below the radius but had different local gain." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_limiter_guard.py", "files": [ "stage2_limiter_guard.py", "bench_report.json" ], "limitations": "Only the built-in dynamics track was tested; no Arnoldi Jacobian continuation, stationary-state bifurcation scan, epsilon sweep, or persistent-oscillation trajectory analysis was performed. The benchmark used three shared learning rates and one clipping radius, 12 epochs, and 400/160 train/test samples.", "system_verdict": "failed", "practical_verdict": "inconclusive", "mechanism_ok": 0, "system_judged": true }