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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Two-sided conditioned DFA was implemented as the training-update intervention on the registered tabular Friedman regression track with the shared mlp_tiny architecture. The idea was significantly worse than tuned raw DFA: test MSE 22.2062 versus 17.4778, paired delta +4.7284, permutation p=0.0081, and 0/8 paired wins. Therefore the benchmark system correctly yields worked=false.",
  "metrics": {
    "baseline": "Raw DFA, best lr=0.001: test MSE 17.477807760238647 +/- 1.5610336422417328 over 8 seeds.",
    "idea": "Two-sided conditioned DFA, best lr=0.01: test MSE 22.206230878829956 +/- 1.2034773425543663 over 8 seeds.",
    "mechanism_signature": "Not confirmed across all trained seeds; mean observed conditioned/raw update-norm ratio was 4.144475221633911."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.001
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 17.2008535861969
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 17.275779485702515
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 18.10535430908203
        }
      ],
      "full": {
        "mean": 17.477807760238647,
        "std": 1.5610336422417328,
        "per_seed": [
          18.36859893798828,
          17.082815170288086,
          17.65996551513672,
          15.692034721374512,
          14.8045015335083,
          18.059467315673828,
          17.911405563354492,
          20.24367332458496
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 22.206230878829956,
      "std": 1.2034773425543663,
      "per_seed": [
        22.064266204833984,
        22.58884048461914,
        20.288148880004883,
        21.367250442504883,
        21.962797164916992,
        21.877431869506836,
        22.725826263427734,
        24.775285720825195
      ],
      "n": 8,
      "selected_cfg": {
        "lr": 0.01
      }
    },
    "comparison": {
      "delta_mean": 4.728423118591309,
      "idea_wins": 0,
      "n_pairs": 8,
      "per_seed_diffs": [
        3.695667266845703,
        5.506025314331055,
        2.628183364868164,
        5.675215721130371,
        7.158295631408691,
        3.817964553833008,
        4.814420700073242,
        4.531612396240234
      ],
      "p_value": 0.0081,
      "mde": 1.172236051535733,
      "mde_rel_pct": 6.70699705372962,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "Factorized Cholesky-preconditioned outer product equals the matrix-form two-sided update when evaluated on trained benchmark models.",
      "confirmed": false,
      "mean_observed_norm_ratio": 4.144475221633911,
      "trained_model_signature_seeds": 8
    },
    "track_rationale": "Two-sided conditioning is an optimizer/update-rule idea; tabular is the prescribed registered optimizer track.",
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.001
        },
        "mean": 200.41951751708984
      },
      {
        "cfg": {
          "lr": 0.003
        },
        "mean": 104.71292400360107
      },
      {
        "cfg": {
          "lr": 0.01
        },
        "mean": 22.206230878829956
      }
    ],
    "selected_idea_cfg": {
      "lr": 0.01
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "Only the registered tabular Friedman regression track was tested, using mlp_tiny, 400 training samples, 400 test samples, 12 epochs, and the shared three-value learning-rate grid. Activity-only and error-only ablations, broader damping and beta sweeps, larger datasets, other architectures, wall-clock normalization, and FLOP accounting were not tested.",
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}