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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "The matched dynamics/rnn_small benchmark was completed using the registered built-in track, with the Martingale Response Control Variate implemented as a local optimizer training loop. The idea was significantly worse than the tuned baseline on standard test MSE (paired delta +0.0610111, permutation p=0.0081), and the trained-model mechanism signature was not confirmed (correlation 0.3859).",
  "metrics": {
    "baseline": "Mean test MSE 0.000587177, std 0.000188147, best lr=0.01 and weight_decay=0.0001.",
    "idea": "Mean test MSE 0.0615982, std 0.0262285, best tested setting lr=0.01 and B=0.01; 0/8 paired wins."
  },
  "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": 0.0001
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0
          },
          "mean": 0.00189586917986162
        },
        {
          "cfg": {
            "lr": 0.001,
            "weight_decay": 0.0001
          },
          "mean": 0.0018708228308241814
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0
          },
          "mean": 0.0011934205977013335
        },
        {
          "cfg": {
            "lr": 0.003,
            "weight_decay": 0.0001
          },
          "mean": 0.0011638484720606357
        },
        {
          "cfg": {
            "lr": 0.01,
            "weight_decay": 0.0
          },
          "mean": 0.0006797004389227368
        },
        {
          "cfg": {
            "lr": 0.01,
            "weight_decay": 0.0001
          },
          "mean": 0.0006384092921507545
        }
      ],
      "full": {
        "mean": 0.0005871770044905134,
        "std": 0.00018814704891426874,
        "per_seed": [
          0.0005189243238419294,
          0.0004705469182226807,
          0.0005624755285680294,
          0.0010016903979703784,
          0.00043606097460724413,
          0.0003590150736272335,
          0.000709059473592788,
          0.0006396433454938233
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.06159823667258024,
      "std": 0.026228543789162298,
      "per_seed": [
        0.03603016957640648,
        0.060704488307237625,
        0.07128579169511795,
        0.12067421525716782,
        0.036086555570364,
        0.05306970328092575,
        0.04153890535235405,
        0.07339606434106827
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.06101105966808973,
      "idea_wins": 0,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.03551124525256455,
        0.060233941389014944,
        0.07072331616654992,
        0.11967252485919744,
        0.035650494595756754,
        0.05271068820729852,
        0.04082984587876126,
        0.07275642099557444
      ],
      "p_value": 0.0081,
      "mde": 0.023317468523288972,
      "mde_rel_pct": 3971.114049931378,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "mechanism_signature": {
      "predicted_vs_observed_response_energy_correlation": 0.3858615399466485,
      "n_events": 71,
      "mean_predicted_q": 0.004985458278228385,
      "mean_observed_response_energy": 0.17620386219206127,
      "confirmed": false
    },
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.003,
          "B": 0.01
        },
        "result": {
          "mean": 0.4648762457072735,
          "std": 0.07276913610879036,
          "per_seed": [
            0.43023642897605896,
            0.48516616225242615,
            0.4949433505535126,
            0.6188828349113464,
            0.35503676533699036,
            0.45395129919052124,
            0.40333887934684753,
            0.4774542450904846
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.01,
          "B": 0.002
        },
        "result": {
          "mean": 0.07644666079431772,
          "std": 0.029671290679075483,
          "per_seed": [
            0.04703869670629501,
            0.07580636441707611,
            0.08537329733371735,
            0.1421934962272644,
            0.04514418542385101,
            0.06873445212841034,
            0.05466177314519882,
            0.09262102097272873
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.01,
          "B": 0.01
        },
        "result": {
          "mean": 0.06159823667258024,
          "std": 0.026228543789162298,
          "per_seed": [
            0.03603016957640648,
            0.060704488307237625,
            0.07128579169511795,
            0.12067421525716782,
            0.036086555570364,
            0.05306970328092575,
            0.04153890535235405,
            0.07339606434106827
          ],
          "n": 8
        }
      }
    ]
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_martingale.py",
  "files": [
    "bench_martingale.py",
    "bench_report.json"
  ],
  "limitations": "Only the registered built-in dynamics track was tested with 400 training examples, 100 test examples, 18 epochs, three idea settings, and six baseline configurations. The implementation used the current gradient as a local response estimate rather than an explicit differentiable future rollout; Adam, global clipping, larger datasets, and compute overhead were not tested.",
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}