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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented an end-to-end finite-splitting directional CNN on the structurally matched CIFAR-10 vision track, with dense and top-2 routed systems sharing the same architecture and training protocol. The mathematical check passed exactly: lacunarity ratio 0.5 and binary-tree split bound 3 for K=8, N=3. Routing confirmed 4x fewer directional samples, but the task-metric improvement was not significant (paired delta -0.01125, permutation p=0.18755), so there is no demonstrated benchmark win.",
  "metrics": {
    "baseline": "CIFAR-10 error mean 0.850625, std 0.038523; best lr=0.001 after sweep over 0.001, 0.003, 0.005.",
    "idea": "Top-2 routed directional CNN error mean 0.839375, std 0.035920; best lr=0.003; paired delta=-0.011250; 4/8 paired wins; permutation p=0.18755; observed directional-sample reduction 4.0x versus dense and predicted 4.0x."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "vision",
    "model": "directional_cnn",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.001
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.8287499845
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.838749975
        },
        {
          "cfg": {
            "lr": 0.005
          },
          "mean": 0.8549999893
        }
      ],
      "full": {
        "mean": 0.8506249711,
        "std": 0.0385225254,
        "per_seed": [
          0.7999999523,
          0.8849999905,
          0.8249999881,
          0.7999999523,
          0.8399999738,
          0.8599999547,
          0.9099999666,
          0.8849999905
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.8393749893,
      "std": 0.0359198349,
      "per_seed": [
        0.8149999976,
        0.8849999905,
        0.8050000072,
        0.7749999762,
        0.8399999738,
        0.8700000048,
        0.875,
        0.8499999642
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.0112499818,
      "idea_wins": 4,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.0150000453,
        0.0,
        -0.0199999809,
        -0.0249999762,
        0.0,
        0.0100000501,
        -0.0349999666,
        -0.0350000262
      ],
      "p_value": 0.18755,
      "mde": 0.0166857148,
      "mde_rel_pct": 1.9615830011,
      "verdict": "no significant win",
      "system_worked": false
    },
    "math_check": {
      "geometric_ratio": 0.5,
      "expected_ratio": 0.5,
      "ratio_allclose": true,
      "K": 8,
      "M": 2,
      "path_split_counts": [
        3,
        3,
        3,
        3,
        3,
        3,
        3,
        3
      ],
      "max_splits": 3,
      "N": 3,
      "bound_holds": true
    },
    "mechanism_signature": {
      "prediction": "top-2 of K=8 uses 4x fewer directional samples",
      "K": 8,
      "beam": 2,
      "predicted_reduction": 4.0,
      "observed_reduction": [
        4.0,
        4.0
      ],
      "confirmed": true
    },
    "structural_match": "spatial CIFAR images and convolutional directional fields"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the fixed vision track was tested, using 400 training and 200 test CIFAR-10 examples, K=8 rather than the proposed K=32, beam width 2, and 5 epochs. The implementation uses differentiable grid sampling rather than a production fused routing kernel; end-to-end wall-clock speedup was not established. The mechanism prediction was confirmed, but it did not produce a statistically significant task-metric win under the required 8-seed protocol.",
  "system_verdict": "partial",
  "practical_verdict": "no_effect",
  "mechanism_ok": 1,
  "system_judged": true
}