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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "The Schur layerwise trust-scaled Adam intervention was tested against tuned Adam on the structurally matched registered tabular/Friedman#1 track using the shared mlp_tiny architecture. The Schur identity sanity check passed, but the idea significantly worsened test MSE: 6.39675 versus 6.07836, paired delta +0.31839, permutation p=0.03725; therefore the benchmark system verdict is not a win. The trained-model mechanism signature was also not confirmed, with predicted shrinkage 1.60444 versus observed 0.58791.",
  "metrics": {
    "baseline": "best_cfg={lr:0.006, weight_decay:0.0001}; full_mean=6.078357219696045; full_std=0.6427959389730813",
    "idea": "best_cfg={lr:0.006, weight_decay:0.0001}; mean=6.396751523017883; std=0.5465600136268931; per_seed=[5.679222583770752,6.877334117889404,5.647143363952637,6.208988666534424,6.021716594696045,6.866507053375244,6.70987606048584,7.163223743438721]"
  },
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "weight_decay": 0.0001
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0
          },
          "mean": 9.648519039154053
        },
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0001
          },
          "mean": 9.278189897537231
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0
          },
          "mean": 6.7801748514175415
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0001
          },
          "mean": 6.735160827636719
        },
        {
          "cfg": {
            "lr": 0.006,
            "weight_decay": 0.0
          },
          "mean": 6.557140588760376
        },
        {
          "cfg": {
            "lr": 0.006,
            "weight_decay": 0.0001
          },
          "mean": 6.396751523017883
        }
      ],
      "full": {
        "mean": 6.078357219696045,
        "std": 0.6427959389730813,
        "per_seed": [
          5.252819061279297,
          6.84149169921875,
          5.513339042663574,
          5.129052639007568,
          6.107614517211914,
          6.495948314666748,
          6.7050628662109375,
          6.58152961730957
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 6.396751523017883,
      "std": 0.5465600136268931,
      "per_seed": [
        5.679222583770752,
        6.877334117889404,
        5.647143363952637,
        6.208988666534424,
        6.021716594696045,
        6.866507053375244,
        6.70987606048584,
        7.163223743438721
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.3183943033218384,
      "idea_wins": 1,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.4264035224914551,
        0.0358424186706543,
        0.1338043212890625,
        1.0799360275268555,
        -0.08589792251586914,
        0.3705587387084961,
        0.004813194274902344,
        0.5816941261291504
      ],
      "p_value": 0.03725,
      "mde": 0.32219506919545965,
      "mde_rel_pct": 5.300693222692354,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "math_verification": {
      "max_abs_hessian_error": 1.0704046315979099e-08,
      "min_R_eigenvalue": 0.052625321728098556,
      "identity_pass": true
    },
    "mechanism_signature": {
      "quantity": "Schur trust shrinkage measured during trained MLP updates",
      "predicted_vs_observed": {
        "predicted_mean_shrink": 1.6044402480254512,
        "observed_mean_shrink": 0.5879142193063809,
        "relative_error": 1.7290380047562637
      },
      "max_R_eigenvalue_mean": 22.230229174028956,
      "confirmed": false
    },
    "protocol_note": "Registered built-in tabular track; 8 paired seeds; baseline sweep included every learning rate tried by the idea and both weight-decay values."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 schur_bench.py",
  "files": [
    "schur_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the registered tabular optimizer track was tested; vision, sequence, and dynamics were not tested. The implementation uses a measured controller proxy rather than full implicit Hessian/Jacobian-vector-product differentiation. Runtime/FLOP overhead, alternative mechanism amplitudes, momentum mechanisms, and larger models were not evaluated.",
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}