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

(универсальный)

Ответ агента:

{
  "worked": true,
  "confidence": 8,
  "verdict": "Implemented the null-space-preserving consensus optimizer as a local four-replica MLP training loop on the structurally matched tabular optimizer track. The rebuilt-degree idea significantly improved test MSE over the stale-degree baseline, with paired delta -0.003935, permutation p=0.0081, and 8/8 paired wins. The trained-model mechanism signature was confirmed by predicted/observed forcing correlation 0.987 and preserved null-space residual 2.02e-7.",
  "metrics": {
    "baseline": "Best stale-degree baseline lr=0.006 gamma=0.05; full 8-seed MSE 15.977716 +/- 1.628230.",
    "idea": "Best rebuilt-degree idea lr=0.006 gamma=0.05; full 8-seed MSE 15.973781 +/- 1.627115; paired delta=-0.003935; permutation p=0.0081; 8/8 wins.",
    "mechanism": "Predicted forcing mean 0.00317219; observed forcing mean 0.00131647; correlation 0.98725; preserved max norm L1=2.02e-7."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "Only the structurally matched tabular Friedman regression track with mlp_tiny was tested. Directed nonsymmetric graphs, quantization, delays, adaptive preconditioners, larger models, communication cost, and distributed hardware execution were not evaluated.",
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "gamma": 0.05
      },
      "full": {
        "mean": 15.977716445922852,
        "std": 1.6282301026629502,
        "per_seed": [
          16.489761352539062,
          12.152153015136719,
          16.143342971801758,
          16.70903778076172,
          15.373194694519043,
          18.03249168395996,
          15.8712797164917,
          17.05047035217285
        ],
        "n": 8
      }
    },
    "idea": {
      "cfg": {
        "lr": 0.006,
        "gamma": 0.05
      },
      "mean": 15.97378134727478,
      "std": 1.6271148262155959,
      "per_seed": [
        16.480152130126953,
        12.151780128479004,
        16.140649795532227,
        16.70699691772461,
        15.370565414428711,
        18.029369354248047,
        15.864901542663574,
        17.045835494995117
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.003935098648071289,
      "idea_wins": 8,
      "n_pairs": 8,
      "p_value": 0.0081,
      "mde": 0.0024242191095692803,
      "mde_rel_pct": 0.015172500512035846,
      "verdict": "idea better (significant)",
      "system_worked": true
    },
    "mechanism_signature": {
      "prediction": "common-mode coupling forcing proportional to row-sum defect",
      "trained_samples": 96,
      "predicted_mean": 0.003172187144357496,
      "observed_mean": 0.0013164669848377698,
      "predicted_observed_corr": 0.9872485726198638,
      "preserving_L1_max": 2.0212918469683135e-07,
      "confirmed": true
    },
    "sanity_check": {
      "preserve_max_L1": 2.0212918469683135e-07,
      "baseline_mean_L1": 1.6711764521845454
    }
  },
  "system_verdict": "worked",
  "practical_verdict": "helps",
  "mechanism_ok": 1,
  "system_judged": true
}