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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "The registered built-in dynamics track was benchmarked with rnn_small under the full 8-seed paired protocol. The Lyapunov intervention produced a small lower MSE, but the paired permutation test was not significant, and the trained-model gradient-energy ratio contradicted the predicted contraction; therefore the system did not work.",
  "metrics": {
    "baseline": "Best tuned Adam baseline lr=0.01: test MSE 0.0015652803 ± 0.0007422460 over 8 seeds.",
    "idea": "Best finite-horizon regularized model lr=0.01, M=4, alpha=0.1, lambda=0.002, beta=0.9: test MSE 0.0015269540 ± 0.0007877648; paired delta=-0.0000383263, p=0.46705.",
    "mechanism": "Trained-model mean V[k+4]/V[k]=1.827379, violation rate=0.039474; contraction prediction was not confirmed."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_stage2.py",
  "files": [
    "bench_stage2.py",
    "bench_report.json"
  ],
  "limitations": "The final protocol used 800 training samples, 300 test samples, and 6 epochs to fit the runtime budget. Baseline and idea used the same three learning rates and all 8 paired seeds. Only the gradient certificate was tested; hidden-state certificates, other M values, lambda sweeps, and longer training were not tested.",
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.015694387606345117
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.0023102034465409815
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 0.0013842678163200617
        }
      ],
      "full": {
        "mean": 0.0015652802903787233,
        "std": 0.0007422459790989128,
        "per_seed": [
          0.0013847877271473408,
          0.0011940097901970148,
          0.0015944147016853094,
          0.0013638590462505817,
          0.0008487981976941228,
          0.000910585920792073,
          0.001885351026430726,
          0.0033404359128326178
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.0015269540235749446,
      "std": 0.000787764827387549,
      "per_seed": [
        0.0010921545326709747,
        0.0012567200465127826,
        0.0015678050694987178,
        0.0012287304271012545,
        0.0008476584334857762,
        0.0009015121031552553,
        0.0018893856322392821,
        0.0034316659439355135
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -3.832626680377871e-05,
      "idea_wins": 5,
      "n_pairs": 8,
      "per_seed_diffs": [
        -0.00029263319447636604,
        6.271025631576777e-05,
        -2.6609636591621626e-05,
        -0.00013512861914932728,
        -1.1397642083466053e-06,
        -9.073817636817694e-06,
        4.03460580855608e-06,
        9.123003110289574e-05
      ],
      "p_value": 0.46705,
      "mde": 0.00010250800277371827,
      "mde_rel_pct": 6.548859230120136,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "Finite-horizon gradient energy should contract on average and persistent instability should produce positive residual violations.",
      "trained_model_measurements": {
        "idea_cfg": {
          "lr": 0.01
        },
        "observed_mean_v_ratio": 1.8273790166958381,
        "observed_violation_rate": 0.039473684210526314,
        "per_seed_summary": "Eight trained idea models; mean V[k+4]/V[k] measured as 1.827379 and mean violation rate measured as 0.039474."
      },
      "confirmed": false,
      "certificate": {
        "M": 4,
        "alpha": 0.1,
        "lambda": 0.002,
        "beta": 0.9
      }
    }
  },
  "system_verdict": "failed",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 0,
  "system_judged": true
}