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

(универсальный)

Ответ агента:

{
  "worked": true,
  "confidence": 8,
  "verdict": "Implemented Green-Margin Residual Dynamics on the structurally matched dynamics track using the shared rnn_small GRU architecture. The intervention projects the recurrent perturbation so the measured Green estimate satisfies q=Gamma||W_hh||2<=0.8. Across 8 paired seeds it significantly improved test MSE: 0.00057228 versus baseline 0.00208631, paired delta=-0.00151403, permutation p=0.0081; the trained-model mechanism signature confirmed q≈0.8000.",
  "metrics": {
    "baseline": "test MSE mean 0.00208631, std 0.00045501, tuned lr=0.006; sweep means lr=0.001: 0.00410370, lr=0.003: 0.00338617, lr=0.006: 0.00169839",
    "idea": "test MSE mean 0.00057228, std 0.00029326, tuned lr=0.006; idea sweep means lr=0.001: 0.23657939, lr=0.003: 0.00440150, lr=0.006: 0.00057228; q estimate 0.78160",
    "comparison": "paired delta=-0.00151403, 8/8 idea wins, permutation p=0.0081, verdict idea better (significant)",
    "mechanism_signature": "trained-model observed recurrent gain 0.159998, Gamma=5, observed q=0.799992, predicted response bound 4.9998, observed input sensitivity 0.3732, confirmed=true"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_green_margin.py",
  "files": [
    "bench_green_margin.py",
    "bench_report.json"
  ],
  "limitations": "Only the built-in dynamics track and rnn_small GRU were tested. The implementation constrains the GRU recurrent matrix spectral norm as a practical Green-margin proxy rather than estimating the full nonautonomous transition kernel or per-layer Jacobian margins. The run used 12 epochs, 400 training examples, 400 test examples, one small learning-rate grid, and no longer-horizon rollout, non-diagonal backbone, FLOP/speed, or target-margin ablation.",
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.004103701037820429
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.0033861721749417484
        },
        {
          "cfg": {
            "lr": 0.006
          },
          "mean": 0.0016983873210847378
        }
      ],
      "full": {
        "mean": 0.0020863086683675647,
        "std": 0.00045500750701757853,
        "per_seed": [
          0.0018287990242242813,
          0.0014274335699155927,
          0.0014271392719820142,
          0.002110177418217063,
          0.002619170816615224,
          0.0024625908117741346,
          0.002196874236688018,
          0.00261828419752419
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.0005722835539927473,
      "std": 0.0002932567715427045,
      "per_seed": [
        0.000741662981454283,
        0.0004835625004488975,
        0.00047368029481731355,
        0.00031156351906247437,
        0.0005250111571513116,
        0.0005999802378937602,
        0.0002084407169604674,
        0.001234367024153471
      ],
      "n": 8,
      "final_recurrent_gain": 0.15632064081728458,
      "q_estimate": 0.781603204086423,
      "q_target": 0.8
    },
    "comparison": {
      "delta_mean": -0.0015140251143748173,
      "idea_wins": 8,
      "n_pairs": 8,
      "per_seed_diffs": [
        -0.0010871360427699983,
        -0.0009438710694666952,
        -0.0009534589771647006,
        -0.0017986138991545886,
        -0.0020941596594639122,
        -0.0018626105738803744,
        -0.0019884335197275504,
        -0.001383917173370719
      ],
      "p_value": 0.0081,
      "mde": 0.0004000819361453537,
      "mde_rel_pct": 19.176545743751255,
      "verdict": "idea better (significant)",
      "system_worked": true
    },
    "protocol": {
      "paired_seeds": [
        0,
        1,
        2,
        3,
        4,
        5,
        6,
        7
      ],
      "epochs": 12,
      "batch": 128,
      "q0": 0.8,
      "grid": [
        {
          "lr": 0.001
        },
        {
          "lr": 0.003
        },
        {
          "lr": 0.006
        }
      ],
      "idea_sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.2365793865174055
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.004401497146318434
        },
        {
          "cfg": {
            "lr": 0.006
          },
          "mean": 0.0005722835539927473
        }
      ]
    },
    "mechanism_signature": {
      "trained_model": true,
      "backbone_gamma": 5.000000000000001,
      "observed_recurrent_gain": 0.15999846160411835,
      "observed_q": 0.7999923080205918,
      "predicted_green_response_bound": 4.99980770791033,
      "observed_input_sensitivity": 0.373172789812088,
      "baseline_test_mse_seed0": 0.0018287990242242813,
      "idea_test_mse_seed0": 0.0006890770746394992,
      "confirmed": true
    },
    "custom_track": null
  },
  "system_verdict": "worked",
  "practical_verdict": "helps",
  "mechanism_ok": 1,
  "system_judged": true
}