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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Implemented the Phi^2-inspired differentiable feature stabilizer in a matched small CNN and ran the full 8-seed vision benchmark with baseline and idea learning-rate sweeps. The baseline error was 0.70417 versus 0.75833 for the best idea setting; paired delta was +0.05417 with permutation p=0.0169, meaning the idea was significantly worse. The trained-model mechanism signature was also not confirmed: observed high-frequency and low-frequency ratios were 7.594 and 16.193 versus predicted 0.5625 and 1.0.",
  "metrics": {
    "baseline": "vision cnn_small error mean=0.7041667; best lr=0.002; per-seed=[0.7166667,0.7000000,0.6416667,0.6833334,0.7166667,0.7250000,0.7916667,0.6583334]",
    "idea": "vision stabilized cnn_small error mean=0.7583334; best lr=0.001 alpha=0.75; per-seed=[0.7500001,0.7416667,0.7500001,0.7083334,0.7666667,0.7750000,0.7750000,0.8000001]",
    "comparison": {
      "delta_mean": 0.0541667,
      "p_value": 0.0169,
      "verdict": "idea worse (significant)",
      "idea_wins": 1,
      "n_pairs": 8
    },
    "mechanism_signature": {
      "predicted_high_ratio": 0.5625,
      "observed_high_ratio": 7.5937355,
      "predicted_degree2_ratio": 1.0,
      "observed_degree2_ratio": 16.1934479,
      "confirmed": false
    }
  },
  "bench_report": {
    "bench_version": 1,
    "track": "vision",
    "model": "cnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.002,
        "alpha": 0.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "alpha": 0.0
          },
          "mean": 0.6916667
        },
        {
          "cfg": {
            "lr": 0.002,
            "alpha": 0.0
          },
          "mean": 0.6854167
        },
        {
          "cfg": {
            "lr": 0.003,
            "alpha": 0.0
          },
          "mean": 0.7083334
        },
        {
          "cfg": {
            "lr": 0.004,
            "alpha": 0.0
          },
          "mean": 0.7041667
        },
        {
          "cfg": {
            "lr": 0.006,
            "alpha": 0.0
          },
          "mean": 0.7041667
        }
      ],
      "full": {
        "mean": 0.7041667,
        "std": 0.0431003,
        "per_seed": [
          0.7166667,
          0.7,
          0.6416667,
          0.6833334,
          0.7166667,
          0.725,
          0.7916667,
          0.6583334
        ],
        "n": 8
      }
    },
    "idea": {
      "config": {
        "lr": 0.001,
        "alpha": 0.75
      },
      "mean": 0.7583334,
      "std": 0.0256851,
      "per_seed": [
        0.7500001,
        0.7416667,
        0.7500001,
        0.7083334,
        0.7666667,
        0.775,
        0.775,
        0.8000001
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.0541667,
      "idea_wins": 1,
      "n_pairs": 8,
      "p_value": 0.0169,
      "mde": 0.041307,
      "mde_rel_pct": 5.8661,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "structural_match": "vision feature-map normalization / convolutional spatial angular field",
    "idea_sweep": [
      {
        "config": {
          "lr": 0.001,
          "alpha": 0.75
        },
        "mean": 0.7583334
      },
      {
        "config": {
          "lr": 0.003,
          "alpha": 1.0
        },
        "mean": 0.7697917
      },
      {
        "config": {
          "lr": 0.006,
          "alpha": 1.0
        },
        "mean": 0.8447917
      }
    ],
    "custom_track": null,
    "mechanism_signature": {
      "predicted_high_ratio": 0.5625,
      "observed_high_ratio": 7.5937355,
      "predicted_degree2_ratio": 1.0,
      "observed_degree2_ratio": 16.1934479,
      "tolerance": 0.25,
      "confirmed": false,
      "measurement": "trained vision CNN intermediate feature maps; 2D Fourier high/low proxies"
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py",
  "files": [
    "bench_experiment.py",
    "bench_report.json"
  ],
  "limitations": "The built-in vision benchmark is only a structural proxy for spherical directional fields; no ModelNet40 or true spherical CNN was tested. The spatial Fourier signature is a proxy rather than an exact spherical-harmonic decomposition, and the small 12-epoch CIFAR subset limits statistical power beyond the required 8 paired seeds.",
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}