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

(универсальный)

Ответ агента:

{
  "worked": true,
  "confidence": 8,
  "verdict": "Implemented shared-private matrix-weighted coupling on the structurally matched dynamics track using four identical GRU experts and A_ij=UU^T. Across 8 paired seeds, test MSE improved from 0.00392444 to 0.00368556, with paired delta -0.00023888 and permutation p=0.0081; shared disagreement decreased while private variance remained nonzero. CUDA cuDNN allocation failed in the shared environment, and the implemented CPU fallback completed the run.",
  "metrics": {
    "baseline": "Dynamics four-independent-expert baseline, lr=0.01, wd=0.0001, 12 epochs: test MSE 0.0039244446 ± 0.0009507399.",
    "idea": "Shared-private rank=8, coupling=0.03, same lr/wd/epochs: test MSE 0.0036855603 ± 0.0008949623; paired delta -0.0002388843; permutation p=0.0081; 8/8 paired wins. Shared disagreement 0.0204189 vs baseline 0.0651100; private variance 0.0840237 vs 0.0804247; mechanism confirmed=true."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py",
  "files": [
    "bench_experiment.py",
    "bench_report.json"
  ],
  "limitations": "The requested bench README was absent. Only the dynamics track was tested. The intervention required a custom multi-expert training loop rather than bench.train_model. The shared basis was fixed rather than learned, and CUDA failed due to cuDNN host-allocation pressure, so final results came from the automatic CPU fallback. The baseline was independent experts with the same custom GRU architecture, not the single-model built-in rnn_small path.",
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01,
        "wd": 0.0001,
        "epochs": 12,
        "batch": 128,
        "rank": 8,
        "coupling": 0.0
      },
      "sweep_means": [
        0.0191012383,
        0.0053477885,
        0.0039304872
      ],
      "full_mean": 0.0039244446,
      "full_std": 0.0009507399
    },
    "idea": {
      "best_cfg": {
        "lr": 0.01,
        "wd": 0.0001,
        "epochs": 12,
        "batch": 128,
        "rank": 8,
        "coupling": 0.03
      },
      "mean": 0.0036855603,
      "std": 0.0008949623,
      "per_seed": [
        0.0049509322,
        0.0027915509,
        0.0026541445,
        0.0039238823,
        0.0043672905,
        0.003135113,
        0.0048497785,
        0.0028117904
      ]
    },
    "comparison": {
      "delta_mean": -0.0002388843,
      "idea_wins": 8,
      "n_pairs": 8,
      "p_value": 0.0081,
      "verdict": "idea better (significant)"
    },
    "mechanism_signature": {
      "observed_idea_shared_disagreement_mean": 0.0204189165,
      "observed_baseline_shared_disagreement_mean": 0.0651100194,
      "observed_idea_private_variance_mean": 0.0840237327,
      "observed_baseline_private_variance_mean": 0.0804246916,
      "confirmed": true
    }
  },
  "system_verdict": "partial",
  "practical_verdict": "no_effect",
  "mechanism_ok": 1,
  "system_judged": true
}