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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "The graded Levy-area recurrent state was implemented and evaluated on the structurally matched sequence forecasting track with canonical training, matched learning-rate sweeps, and 8 paired seeds. Mean test MSE improved from 1.04215 to 1.01520 with 7/8 wins, but the paired permutation test was non-significant (p=0.21995), so no significant win was established. The trained-model reversal signature confirmed the predicted area contribution quantitatively.",
  "metrics": {
    "baseline": "best lr=0.01; mean test MSE 1.0421477407; std 0.1010176444",
    "idea": "best lr=0.01; mean test MSE 1.0151974857; std 0.0879008312; paired delta -0.0269502550; 7/8 wins; p=0.21995; mechanism confirmed"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the built-in sequence track was tested, using 15 epochs and 400 training/400 test examples. Other tracks were not tested. The idea model had 185 parameters versus 65 for baseline; equal-parameter and equal-FLOP comparisons were not performed.",
  "bench_report": {
    "bench_version": 1,
    "track": "sequence",
    "model": "custom_recurrent_state",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 1.100467175245285
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 1.0823257267475128
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 1.043792873620987
        }
      ],
      "full": {
        "mean": 1.0421477407217026,
        "std": 0.10101764442672699,
        "per_seed": [
          1.1993988752365112,
          0.8459368944168091,
          1.0848031044006348,
          1.0450326204299927,
          1.0629944801330566,
          1.080702543258667,
          1.0881637334823608,
          0.9301496744155884
        ]
      }
    },
    "idea": {
      "best_cfg": {
        "lr": 0.01
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 1.0460671931505203
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 1.0292403250932693
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 1.0069926232099533
        }
      ],
      "full": {
        "mean": 1.0151974856853485,
        "std": 0.08790083123237098,
        "per_seed": [
          1.1760079860687256,
          0.8348132967948914,
          1.027022123336792,
          0.9901270866394043,
          1.0220698118209839,
          0.9881404042243958,
          1.0568915605545044,
          1.0265076160430908
        ]
      }
    },
    "comparison": {
      "delta_mean": -0.026950255036354065,
      "idea_wins": 7,
      "n_pairs": 8,
      "per_seed_diffs": [
        -0.023390889167785645,
        -0.011123597621917725,
        -0.05778098106384277,
        -0.05490553379058838,
        -0.040924668312072754,
        -0.09256213903427124,
        -0.031272172927856445,
        0.09635794162750244
      ],
      "p_value": 0.21995,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "observed_output_reversal_rms": 0.2850640714,
      "predicted_area_head_rms": 0.2850641012,
      "observed_to_predicted_rms_ratio": 0.9999998955,
      "correlation": 0.9999999999999685,
      "confirmed": true
    }
  },
  "system_verdict": "partial",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 1,
  "system_judged": true
}