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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Implemented the Finite-Horizon Lyapunov Risk Monitor on the registered dynamics track using matched recurrent systems and evaluated it with the official bench reporting protocol. The idea achieved lower mean MSE (0.0014701 vs 0.0015849; paired delta -0.0001148) and won 7/8 pairs, but permutation p=0.17025, so this is not a significant win. The trained-model mechanism signature was confirmed: predicted positive-FTLE fraction 6.10e-28 versus observed 0.0.",
  "metrics": {
    "baseline": "Tuned baseline rnn_small: mean test MSE 0.0015848712, std 0.0004409408, best lr 0.003",
    "idea": "Best reported UCB monitor: mean test MSE 0.0014701014, std 0.0005500, paired delta -0.0001147698, 7/8 wins, permutation p=0.17025",
    "mechanism_signature": "Gaussian FTLE prediction: predicted positive fraction 6.103742223005928e-28, observed 0.0, absolute error 6.103742223005928e-28, confirmed=true"
  },
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.003,
        "weight_decay": 0.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0
          },
          "mean": 0.004407020111102611
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0
          },
          "mean": 0.0013896534073865041
        }
      ],
      "full": {
        "mean": 0.0015848711991566233,
        "std": 0.0004409408404879072,
        "per_seed": [
          0.0009277964127250016,
          0.0014898052904754877,
          0.001270615728572011,
          0.0018703961977735162,
          0.0014201324665918946,
          0.001722313230857253,
          0.0014589702477678657,
          0.002518940018489957
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.0014701014006277546,
      "std": 0.0005499829937633325,
      "per_seed": [
        0.0008705478394404054,
        0.0014663755428045988,
        0.0011225328780710697,
        0.0015238631749525666,
        0.0013210882898420095,
        0.0013340504374355078,
        0.0012874765088781714,
        0.0028348765335977077
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.0001147697985288687,
      "idea_wins": 7,
      "n_pairs": 8,
      "per_seed_diffs": [
        -5.7248573284596205e-05,
        -2.34297476708889e-05,
        -0.00014808285050094128,
        -0.00034653302282094955,
        -9.904417674988508e-05,
        -0.0003882627934217453,
        -0.00017149373888969421,
        0.0003159365151077509
      ],
      "p_value": 0.17025,
      "mde": 0.00018161700236817133,
      "mde_rel_pct": 11.459417173131632,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "Gaussian p+=Phi(mu/sd) for finite-horizon FTLE",
      "predicted_positive_fraction": 6.103742223005928e-28,
      "observed_positive_fraction": 0.0,
      "absolute_error": 6.103742223005928e-28,
      "confirmed": true
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_run.py",
  "files": [
    "bench_run.py",
    "bench_report.json"
  ],
  "limitations": "The official README was present on disk but inaccessible through the read tool; its contract and APIs were inspected directly via Python. The implementation used a local GRUCell equivalent to expose hidden states for the intervention rather than bench.make_model's opaque GRU wrapper. The finite-difference FTLE monitor is a directional Jacobian proxy rather than an exact spectral norm, and the three rho settings produced identical reported metrics, indicating the regularization term was effectively inactive or numerically negligible in this short run. The protocol used a reduced 2-value baseline learning-rate sweep and 4 training epochs to fit the runtime budget.",
  "system_verdict": "partial",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 1,
  "system_judged": true
}