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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented a structurally matched custom categorical-joint track and trained identical bidirectional neural conditional systems with and without the log-space four-variable cycle penalty. The mechanism signature was confirmed: mean absolute residual decreased from 0.09545 to 0.05557, but held-out bidirectional NLL was marginally worse (1.75742 vs 1.75698), with paired delta +0.000447 and permutation p=0.76795. The idea therefore did not produce a significant task-metric win.",
  "metrics": {
    "baseline": "8-seed test bidirectional NLL mean=1.756976, std=0.027960; best lr=0.01; lr sweep {0.01, 0.03, 0.08}",
    "idea": "8-seed test bidirectional NLL mean=1.757423, std=0.026287; selected lr=0.03, lambda=1.0; paired delta=+0.000447, p=0.76795; mean |Delta| baseline=0.095445 vs idea=0.055569; p95 |Delta| baseline=0.248574 vs idea=0.138366"
  },
  "bench_report": {
    "bench_version": 1,
    "track": "bidirectional_conditional_joint",
    "model": "bidirectional_mlp",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01,
        "lambda": 0.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.01,
            "lambda": 0.0
          },
          "mean": 1.7526295185
        },
        {
          "cfg": {
            "lr": 0.03,
            "lambda": 0.0
          },
          "mean": 1.7545145452
        },
        {
          "cfg": {
            "lr": 0.08,
            "lambda": 0.0
          },
          "mean": 1.762847513
        }
      ],
      "full": {
        "mean": 1.7569757551,
        "std": 0.0279599736,
        "per_seed": [
          1.7359287739,
          1.8102735281,
          1.7168221474,
          1.7474936247,
          1.7584006786,
          1.7861531973,
          1.7631640434,
          1.7375700474
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 1.7574231178,
      "std": 0.0262865177,
      "per_seed": [
        1.7347164154,
        1.8033754826,
        1.718865633,
        1.745238781,
        1.7678794861,
        1.786344408,
        1.7626433372,
        1.7403213978
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.0004473627,
      "idea_wins": 4,
      "n_pairs": 8,
      "p_value": 0.76795,
      "verdict": "no measurable effect",
      "system_worked": false
    },
    "custom_track": {
      "name": "bidirectional_conditional_joint",
      "file": "cycle_track.py",
      "domain": "conditional_compatibility"
    },
    "mechanism_signature": {
      "quantity": "four-variable log compatibility residual measured on trained neural outputs",
      "idea_mean_abs_delta": 0.0555686555,
      "idea_p95_abs_delta": 0.1383657316,
      "baseline_mean_abs_delta": 0.0954454336,
      "baseline_p95_abs_delta": 0.2485735118,
      "prediction": "cycle regularization lowers compatibility residual",
      "confirmed": true
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_cycle.py",
  "files": [
    "cycle_track.py",
    "bench_cycle.py",
    "bench_report.json"
  ],
  "limitations": "Only the custom categorical conditional-compatibility track was tested; no MNIST, larger models, calibration, sampling consistency, or external bidirectional-imputation dataset was evaluated. The benchmark used 400 training and 400 test samples, a fixed 6x6 synthetic joint, 45 epochs, and three learning rates crossed with three cycle-loss strengths.",
  "system_verdict": "partial",
  "practical_verdict": "no_effect",
  "mechanism_ok": 1,
  "system_judged": true
}