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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented Centered-Geometry Projection Loss in a shared tabular MLP with a 32-dimensional hidden representation and 8-dimensional learned bottleneck. The full 8-seed comparison yielded a tiny improvement in test MSE, 7.631358 versus 7.655009, but paired delta was -0.023651 with permutation p=0.9445, giving no measurable effect. The trained-model signature observed centered-distance correlation 0.999976 but variance ratio 98.0545 versus the reported <=1 ceiling, so the mechanism prediction was not confirmed.",
  "metrics": {
    "baseline": "Registered tabular/mlp track; tuned baseline lr=0.01; full mean test MSE 7.6550092101, std 0.7549298959.",
    "idea": "Selected lr=0.01, lambda=0.03; full mean test MSE 7.6313580275, std 0.8269721814; paired delta -0.0236511827, p=0.9445, idea wins 4/8.",
    "mechanism_signature": {
      "observed_centered_distance_correlation": 0.9999756813,
      "observed_centered_variance_ratio": 98.0545272827,
      "predicted_variance_ceiling": 1.0,
      "confirmed": false
    }
  },
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 17.0065875053
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 11.7050991058
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 7.4261586666
        }
      ],
      "full": {
        "mean": 7.6550092101,
        "std": 0.7549298959,
        "per_seed": [
          7.1253771782,
          6.5090332031,
          7.52886343,
          8.5413608551,
          7.8146495819,
          6.9143929482,
          8.8882131577,
          7.9181833267
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 7.6313580275,
      "std": 0.8269721814,
      "per_seed": [
        7.1351819038,
        6.1604094505,
        7.6477060318,
        8.5403356552,
        7.8442821503,
        6.9134554863,
        8.8934669495,
        7.9160265923
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.0236511827,
      "idea_wins": 4,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.0098047256,
        -0.3486237526,
        0.1188426018,
        -0.0010251999,
        0.0296325684,
        -0.0009374619,
        0.0052537918,
        -0.0021567345
      ],
      "p_value": 0.9445,
      "mde": 0.1149067143,
      "mde_rel_pct": 1.50106565698,
      "verdict": "no measurable effect",
      "system_worked": false
    },
    "track_reason": "tabular is the registered optimizer/regularizer track; both systems share the same MLP and learned bottleneck",
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.001,
          "lambda": 0.03
        },
        "mean_first4": 17.1348912716
      },
      {
        "cfg": {
          "lr": 0.001,
          "lambda": 0.1
        },
        "mean_first4": 17.2414381504
      },
      {
        "cfg": {
          "lr": 0.001,
          "lambda": 0.3
        },
        "mean_first4": 17.4011166096
      },
      {
        "cfg": {
          "lr": 0.003,
          "lambda": 0.03
        },
        "mean_first4": 11.6997609138
      },
      {
        "cfg": {
          "lr": 0.003,
          "lambda": 0.1
        },
        "mean_first4": 11.71778512
      },
      {
        "cfg": {
          "lr": 0.003,
          "lambda": 0.3
        },
        "mean_first4": 11.6664907932
      },
      {
        "cfg": {
          "lr": 0.01,
          "lambda": 0.03
        },
        "mean_first4": 7.3709082603
      },
      {
        "cfg": {
          "lr": 0.01,
          "lambda": 0.1
        },
        "mean_first4": 7.3767888546
      },
      {
        "cfg": {
          "lr": 0.01,
          "lambda": 0.3
        },
        "mean_first4": 7.3780637978
      }
    ],
    "selected_idea_cfg": {
      "lr": 0.01,
      "lambda": 0.03
    },
    "mechanism_signature": {
      "predicted_centered_distance_correlation": "no universal value for learned encoder",
      "observed_centered_distance_correlation": 0.9999756813,
      "observed_centered_variance_ratio": 98.0545272827,
      "predicted_variance_ceiling": 1.0,
      "confirmed": false
    },
    "budget": {
      "epochs": 24,
      "n_train": 400,
      "n_test": 200,
      "batch": 128,
      "hidden_dim": 32,
      "bottleneck_dim": 8,
      "baseline_grid": [
        0.001,
        0.003,
        0.01
      ],
      "idea_lambdas": [
        0.03,
        0.1,
        0.3
      ],
      "seeds": [
        0,
        1,
        2,
        3,
        4,
        5,
        6,
        7
      ]
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the registered tabular track was tested; vision, sequence, and dynamics were not tested. The compact run used 400 training samples, 200 test samples, and 24 epochs. The mechanism signature was measured on the trained idea model, but the Gaussian rank-sketch formula does not directly predict behavior for its learned nonlinear encoder.",
  "system_verdict": "failed",
  "practical_verdict": "no_effect",
  "mechanism_ok": 0,
  "system_judged": true
}