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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Built and evaluated Exact Event-Chained Neural ODE as a two-phase GRU with differentiable hidden-state chaining at the midpoint of the registered dynamics benchmark. The tuned baseline achieved test MSE 0.0012192157, while the best chained model achieved 0.0017279689 across 8 paired seeds; delta_mean was +0.0005087533 and permutation p=0.0478, so the idea was significantly worse. The trained-model mechanism signature was not confirmed: final MAE was 0.0249169 for baseline versus 0.0288821 for the idea.", "metrics": { "baseline": "Best configuration lr=0.006, weight_decay=0.0; sweep means for lr 0.001/0.003/0.006 were 0.0062301282/0.0021712419/0.0012843604; full 8-seed mean test MSE=0.0012192157, std=0.0003956460.", "idea": "Best configuration lr=0.006, weight_decay=0.0; sweep means for lr 0.001/0.003/0.006 were 0.0095398796/0.0029446032/0.0017279689; 8-seed mean test MSE=0.0017279689, std=0.0007180697.", "comparison": { "delta_mean": 0.0005087532845209353, "idea_wins": 1, "n_pairs": 8, "per_seed_diffs": [ 0.00037842104211449623, 0.00012539629824459553, 0.00046890188241377473, 0.0014117142418399453, 0.0015212188591249287, 5.729770055040717e-05, 0.0005326939281076193, -0.00042561767622828484 ], "p_value": 0.0478, "verdict": "idea worse (significant)", "system_worked": false }, "mechanism_signature": { "mean_final_mae_baseline": 0.024916854221373796, "mean_final_mae_idea": 0.028882076730951667, "mean_mid_mae_baseline": 0.14118414279073477, "mean_mid_mae_idea": 0.5059058107435703, "confirmed": false } }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.006, "weight_decay": 0.0 }, "sweep": [ { "cfg": { "lr": 0.001, "weight_decay": 0.0 }, "mean": 0.006230128230527043 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0 }, "mean": 0.002171241940231994 }, { "cfg": { "lr": 0.006, "weight_decay": 0.0 }, "mean": 0.0012843603763030842 } ], "full": { "mean": 0.0012192156573291868, "std": 0.00039564599282397535, "per_seed": [ 0.0012357592349871993, 0.0010409202659502625, 0.0009250942966900766, 0.0019356677075847983, 0.0007404002244584262, 0.0008880241075530648, 0.001238464959897101, 0.0017493944615125656 ], "n": 8 } }, "idea": { "best_cfg": { "lr": 0.006, "weight_decay": 0.0 }, "sweep": [ { "cfg": { "lr": 0.001, "weight_decay": 0.0 }, "mean": 0.0095398795674555, "std": 0.0048062533868374535, "per_seed": [ 0.003919485490769148, 0.015250355005264282, 0.006983126979321241, 0.011106450110673904, 0.018466167151927948, 0.009144495241343975, 0.006878075655549765, 0.004570880904793739 ], "n": 8 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0 }, "mean": 0.0029446032422129065, "std": 0.0010129445526691238, "per_seed": [ 0.0025312649086117744, 0.0030189985409379005, 0.002634982345625758, 0.005140002816915512, 0.0038349826354533434, 0.0016688075847923756, 0.0024676918983459473, 0.0022600952070206404 ], "n": 8 }, { "cfg": { "lr": 0.006, "weight_decay": 0.0 }, "mean": 0.001727968941850122, "std": 0.0007180697415224746, "per_seed": [ 0.0016141802771016955, 0.001166316564194858, 0.0013939961791038513, 0.0033473819494247437, 0.002261619083583355, 0.000945321808103472, 0.0017711588880047202, 0.0013237767852842808 ], "n": 8 } ], "per_seed": [ 0.0016141802771016955, 0.001166316564194858, 0.0013939961791038513, 0.0033473819494247437, 0.002261619083583355, 0.000945321808103472, 0.0017711588880047202, 0.0013237767852842808 ], "mean": 0.001727968941850122, "std": 0.0007180697415224746, "n": 8 }, "comparison": { "delta_mean": 0.0005087532845209353, "idea_wins": 1, "n_pairs": 8, "per_seed_diffs": [ 0.00037842104211449623, 0.00012539629824459553, 0.00046890188241377473, 0.0014117142418399453, 0.0015212188591249287, 5.729770055040717e-05, 0.0005326939281076193, -0.00042561767622828484 ], "p_value": 0.0478, "mde": 0.0005549474090830571, "mde_rel_pct": 45.51675544412911, "verdict": "idea worse (significant)", "system_worked": false }, "mechanism_signature": { "mean_final_mae_baseline": 0.024916854221373796, "mean_final_mae_idea": 0.028882076730951667, "mean_mid_mae_baseline": 0.14118414279073477, "mean_mid_mae_idea": 0.5059058107435703, "prediction": "phase chaining improves final/post-event trajectory prediction", "confirmed": false }, "protocol_notes": "400 train/400 test, 8 paired seeds, 18 epochs; midpoint is the known phase boundary." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_run.py", "files": [ "bench_run.py", "bench_report.json" ], "limitations": "The built-in dynamics track has an 8-step pendulum window but no explicit event-conditioned labels or phase-specific controls, so the midpoint was used as the known phase boundary. A separate soft interface-penalty neural baseline, residual-only PINN training, longer training, and larger data were not tested.", "system_verdict": "failed", "practical_verdict": "harms", "mechanism_ok": 0, "system_judged": true }