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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented and reran Weak Koopman Latent Dynamics on the registered built-in dynamics track using the canonical rnn_small architecture and 8 paired seeds. The weak residual mechanism was confirmed at neural-network scale, but independent pendulum test MSE was marginally worse than the tuned baseline and the paired permutation test was not significant. Therefore the idea does not qualify as a benchmark win.",
  "metrics": {
    "baseline": "Mean test MSE 0.0001381416768708732; tuned lr=0.01, weight_decay=0.0.",
    "idea": "Mean test MSE 0.00013874010073777754; best alpha=0.01 at lr=0.01, weight_decay=0.0.",
    "delta_mean": 5.984238669043407e-07,
    "p_value": 0.969
  },
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.01,
        "weight_decay": 0.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0
          },
          "mean": 0.0010981351661030203
        },
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0001
          },
          "mean": 0.0010876548330998048
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0
          },
          "mean": 0.0005773879893240519
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0001
          },
          "mean": 0.0005898331510252319
        },
        {
          "cfg": {
            "lr": 0.01,
            "weight_decay": 0.0
          },
          "mean": 0.00017333678806608077
        },
        {
          "cfg": {
            "lr": 0.01,
            "weight_decay": 0.0001
          },
          "mean": 0.00024068110360531136
        }
      ],
      "full": {
        "mean": 0.0001381416768708732,
        "std": 8.561204737527774e-05,
        "per_seed": [
          0.00027561953174881637,
          0.00025423229089938104,
          6.920921441633254e-05,
          9.428611519979313e-05,
          0.00011270481627434492,
          4.6381595893763006e-05,
          5.4802185331936926e-05,
          0.00019789766520261765
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.00013874010073777754,
      "std": 8.310915831065427e-05,
      "per_seed": [
        0.0002849092415999621,
        0.00024259932979475707,
        6.42913073534146e-05,
        0.00012459092249628156,
        5.412771861301735e-05,
        7.187522714957595e-05,
        8.046071889111772e-05,
        0.00018706634000409395
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 5.984238669043407e-07,
      "idea_wins": 4,
      "n_pairs": 8,
      "per_seed_diffs": [
        9.289709851145744e-06,
        -1.1632961104623973e-05,
        -4.917907062917948e-06,
        3.0304807296488434e-05,
        -5.857709766132757e-05,
        2.5493631255812943e-05,
        2.5658533559180796e-05,
        -1.08313251985237e-05
      ],
      "p_value": 0.969,
      "mde": 2.4517188581434705e-05,
      "mde_rel_pct": 17.74785795046628,
      "verdict": "no measurable effect",
      "system_worked": false
    },
    "mechanism_signature": {
      "weak_koopman": {
        "model_test_mse": 0.0006496671121567488,
        "weak_residual_rms_observed": 0.009801944717764854,
        "weak_scale_predicted_from_observed_B": 0.0648469477891922,
        "relative_residual": 0.15115506668838702,
        "confirmed": true
      },
      "selected_cfg": {
        "lr": 0.01,
        "weight_decay": 0.0,
        "alpha": 0.01
      },
      "baseline_grid": [
        {
          "lr": 0.001,
          "weight_decay": 0.0
        },
        {
          "lr": 0.001,
          "weight_decay": 0.0001
        },
        {
          "lr": 0.003,
          "weight_decay": 0.0
        },
        {
          "lr": 0.003,
          "weight_decay": 0.0001
        },
        {
          "lr": 0.01,
          "weight_decay": 0.0
        },
        {
          "lr": 0.01,
          "weight_decay": 0.0001
        }
      ],
      "idea_grid": [
        {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.01
        },
        {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.03
        },
        {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.1
        }
      ],
      "track_justification": "Actuated pendulum rollout has explicit dynamical stability/control structure."
    },
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.01
        },
        "result": {
          "mean": 0.00013874010073777754,
          "std": 8.310915831065427e-05,
          "per_seed": [
            0.0002849092415999621,
            0.00024259932979475707,
            6.42913073534146e-05,
            0.00012459092249628156,
            5.412771861301735e-05,
            7.187522714957595e-05,
            8.046071889111772e-05,
            0.00018706634000409395
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.03
        },
        "result": {
          "mean": 0.00014541220389219234,
          "std": 8.054320319092932e-05,
          "per_seed": [
            0.0002905830624513328,
            0.0002372498856857419,
            6.000923895044252e-05,
            0.00013045869127381593,
            8.125846943585202e-05,
            6.058422877686098e-05,
            0.00010983884567394853,
            0.000193315208889544
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.01,
          "weight_decay": 0.0,
          "alpha": 0.1
        },
        "result": {
          "mean": 0.00019572334167605732,
          "std": 7.176352745686476e-05,
          "per_seed": [
            0.00028579795616678894,
            0.00025223862030543387,
            0.00010874042345676571,
            0.00025284208822995424,
            0.00021868280600756407,
            6.382106221280992e-05,
            0.00016829039668664336,
            0.00021537338034249842
          ],
          "n": 8
        }
      }
    ]
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_weak_koopman.py",
  "files": [
    "bench_weak_koopman.py",
    "bench_report.json"
  ],
  "limitations": "This benchmark used the built-in actuated pendulum one-step target rather than long-horizon rollout forecasting, and the latent generator was jointly optimized without a separate ridge-update/decoder reconstruction objective. Only the supplied dynamics track and 8-seed protocol were tested; no Lorenz-63, colored noise, multi-step stability projection, decoder, or computational-cost comparison was run.",
  "system_verdict": "failed",
  "practical_verdict": "no_effect",
  "mechanism_ok": 0,
  "system_judged": true
}