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

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 8, "verdict": "Built a structurally matched custom spatial neural-field track and trained two end-to-end coordinate-MLP systems differing only by the added chunked k=2 PHS anchor head. Across 8 paired seeds, the idea reduced MSE from 0.012713 to 0.006530, delta=-0.006183, with all 8 wins and permutation p=0.0081; the benchmark therefore reports a significant win. The trained PHS residual was nonzero and aligned with held-out baseline error correction (mean correlation 0.704), confirming the tested mechanism at NN scale.", "metrics": { "baseline": "Baseline coordinate MLP, lr=0.01 selected by sweep over {0.001, 0.003, 0.01}: mean test MSE 0.0127128037, std 0.0031444912, per-seed [0.0102508850, 0.0145432632, 0.0139772529, 0.0109899705, 0.0170229226, 0.0169589557, 0.0095467241, 0.0084124552].", "idea": "Coordinate MLP plus chunked differentiable k=2 PHS anchor head, lr=0.01 selected from parity sweep: mean test MSE 0.0065301632, std 0.0013944949, per-seed [0.0083841076, 0.0057844375, 0.0060189855, 0.0073700463, 0.0054297075, 0.0089141643, 0.0052020513, 0.0051378058].", "delta_mean": -0.0061826404, "relative_change_percent": -48.64, "permutation_p_value": 0.0081, "idea_wins": 8, "mechanism_signature": { "prediction": "The trained PHS residual should be nonzero and align with held-out error correction.", "observed_mean_residual_rms": 0.1142530991, "observed_mean_correction_correlation": 0.7042187005, "confirmed": true } }, "how_to_run": "OMP_NUM_THREADS=1 /home/maxwelhelp/main/bin/python3 run_bench.py", "files": [ "run_bench.py", "custom_spatial.py", "bench_report.json" ], "limitations": "This stage-2 MVP uses a local 400-sample custom spatial regression track rather than the absent built-in spatial/PDE track. It uses 96 anchors and a dense torch.cdist interaction per batch, not a true FMM; it does not test 10k-1M anchors, wall-clock or peak-memory scaling, projected null-space coefficient constraints, Vecchia-PCG recalibration, coordinate-encoder integration beyond the small MLP, or the built-in tracks. The custom track is registered in-memory by the driver and is not written into the read-only shared bench directory.", "bench_report": { "bench_version": 1, "track": "spatial_anchor_regression", "model": "coordinate_mlp", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.1463788934 }, { "cfg": { "lr": 0.003 }, "mean": 0.0610822188 }, { "cfg": { "lr": 0.01 }, "mean": 0.0124403429 } ], "full": { "mean": 0.0127128037, "std": 0.0031444912, "per_seed": [ 0.010250885, 0.0145432632, 0.0139772529, 0.0109899705, 0.0170229226, 0.0169589557, 0.0095467241, 0.0084124552 ], "n": 8 } }, "idea": { "mean": 0.0065301632, "std": 0.0013944949, "per_seed": [ 0.0083841076, 0.0057844375, 0.0060189855, 0.0073700463, 0.0054297075, 0.0089141643, 0.0052020513, 0.0051378058 ], "n": 8 }, "comparison": { "delta_mean": -0.0061826404, "idea_wins": 8, "n_pairs": 8, "per_seed_diffs": [ -0.0018667774, -0.0087588257, -0.0079582673, -0.0036199242, -0.0115932152, -0.0080447914, -0.0043446729, -0.0032746494 ], "p_value": 0.0081, "mde": 0.0028189356, "mde_rel_pct": 22.1739881, "verdict": "idea better (significant)", "system_worked": true }, "mechanism_signature": { "prediction": "trained PHS residual should be nonzero and align with held-out error correction", "observed_mean_residual_rms": 0.1142530991, "observed_mean_correction_corr": 0.7042187005, "confirmed": true }, "custom_track": { "name": "spatial_anchor_regression", "file": "custom_spatial.py", "domain": "spatial neural field / interpolation" }, "idea_selected_cfg": { "lr": 0.01 }, "idea_sweep": [ { "cfg": { "lr": 0.01 }, "mean": 0.0065301632 }, { "cfg": { "lr": 0.001 }, "mean": 0.1092755161 }, { "cfg": { "lr": 0.003 }, "mean": 0.0223910473 } ] }, "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }