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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Implemented a matched end-to-end SymplecticRNN replacement for the GRU on the structurally appropriate dynamics track, using train_model and 8 paired seeds. The trained symplectic transition preserved the predicted near-unit Jacobian determinant, with log|det J|=0.00388, but test MSE was significantly worse than the tuned GRU baseline: 0.00631 versus 0.00160, paired delta +0.00471 and permutation p=0.0081. The mechanism was confirmed, but the system did not produce a benchmark win.",
  "metrics": {
    "baseline": "rnn_small GRU, best lr=0.005: test MSE 0.0015987288497854024 ± 0.0004723450985826372 over 8 seeds",
    "idea": "SymplecticRNN, best lr=0.005 and step=0.12: test MSE 0.006309549498837441 ± 0.0013831181007421675 over 8 seeds; trained transition log|det J|=0.00387675897218287"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py",
  "files": [
    "bench_experiment.py",
    "bench_report.json"
  ],
  "limitations": "The compact protocol used 400 training examples, 200 test examples, and 12 epochs. The symplectic model was not parameter- or FLOP-matched to the GRU, only one substep configuration was tested, and no longer rollout evaluation beyond the built-in next-angle task metric was performed.",
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.005
      },
      "full": {
        "mean": 0.0015987288497854024,
        "std": 0.0004723450985826372,
        "per_seed": [
          0.0010614258935675025,
          0.0021564248017966747,
          0.001086847041733563,
          0.0018906960031017661,
          0.0020614659879356623,
          0.0012517774011939764,
          0.0011406542034819722,
          0.002140539465472102
        ],
        "n": 8
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.004298779065720737
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.0034615940821822733
        },
        {
          "cfg": {
            "lr": 0.005
          },
          "mean": 0.0015488484350498766
        }
      ]
    },
    "idea": {
      "mean": 0.006309549498837441,
      "std": 0.0013831181007421675,
      "per_seed": [
        0.004766013007611036,
        0.0075876968912780285,
        0.00614228006452322,
        0.005290781147778034,
        0.005994749721139669,
        0.0061586033552885056,
        0.009300675243139267,
        0.005235596559941769
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.004710820649052039,
      "idea_wins": 0,
      "n_pairs": 8,
      "p_value": 0.0081,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "symplectic transition det should remain near 1",
      "observed_idea_log_abs_det": 0.00387675897218287,
      "observed_baseline_log_abs_det": -42.42223358154297,
      "confirmed": true
    }
  },
  "system_verdict": "partial",
  "practical_verdict": "harms",
  "mechanism_ok": 1,
  "system_judged": true
}