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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented delay-aware residual capacity on the registered dynamics track using the standard rnn_small GRU backbone plus gain-admitted residual modules. Across eight paired seeds, the idea reduced mean test MSE from 0.0021058194 to 0.0015729199, but the paired permutation p-value was 0.27195, so it did not achieve a significant benchmark win. The trained-model mechanism signature confirmed observed aggregate gain 8.5828 was below predicted Gmax 32.0555 at delay 0.05, but this does not override the non-significant task-metric result.",
  "metrics": {
    "baseline": "Best tuned rnn_small baseline, lr=0.006: mean MSE 0.002105819425196387; per-seed [0.002004395006224513,0.001437882543541491,0.0015748648438602686,0.002295783953741193,0.0024020641576498747,0.0024898042902350426,0.0020851334556937218,0.0025566271506249905]. Baseline sweep means: lr 0.001=0.004298779065720737, lr 0.003=0.0034615940821822733, lr 0.006=0.0018282315868418664.",
    "idea": "Best delay-aware residual GRU, lr=0.003: mean MSE 0.001572919929458294; per-seed [0.003213837742805481,0.0008874680497683585,0.0005741477361880243,0.0021032660733908415,0.0012076778803020716,0.0005505986046019,0.003468359587714076,0.0005780037608928978]. Idea sweep means: lr 0.001=0.0017012821772368625, lr 0.003=0.001572919929458294, lr 0.006=0.0026669491053326055.",
    "paired_delta_mean": "-0.0005328994957380928 (idea minus baseline; lower is better)",
    "permutation_p_value": 0.27195,
    "idea_wins": "6/8",
    "mechanism_signature": "predicted Gmax=32.05554648664719; observed trained-model aggregate gain=8.582812905311584; active modules=8; delay=0.05; predicted critical delay at observed gain=0.19797074458180686; within boundary=true; confirmed=true"
  },
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "modules": 0,
        "a": 1.0,
        "delay": 0.05
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "modules": 0,
            "a": 1.0,
            "delay": 0.05
          },
          "mean": 0.004298779065720737
        },
        {
          "cfg": {
            "lr": 0.003,
            "modules": 0,
            "a": 1.0,
            "delay": 0.05
          },
          "mean": 0.0034615940821822733
        },
        {
          "cfg": {
            "lr": 0.006,
            "modules": 0,
            "a": 1.0,
            "delay": 0.05
          },
          "mean": 0.0018282315868418664
        }
      ],
      "full": {
        "mean": 0.002105819425196387,
        "std": 0.000389436566226016,
        "per_seed": [
          0.002004395006224513,
          0.001437882543541491,
          0.0015748648438602686,
          0.002295783953741193,
          0.0024020641576498747,
          0.0024898042902350426,
          0.0020851334556937218,
          0.0025566271506249905
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.001572919929458294,
      "std": 0.0011292896441042427,
      "per_seed": [
        0.003213837742805481,
        0.0008874680497683585,
        0.0005741477361880243,
        0.0021032660733908415,
        0.0012076778803020716,
        0.0005505986046019,
        0.003468359587714076,
        0.0005780037608928978
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.0005328994957380928,
      "idea_wins": 6,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.001209442736580968,
        -0.0005504144937731326,
        -0.0010007171076722443,
        -0.00019251788035035133,
        -0.0011943862773478031,
        -0.0019392056856304407,
        0.0013832261320203543,
        -0.0019786233897320926
      ],
      "p_value": 0.27195,
      "mde": 0.0010739516938063096,
      "mde_rel_pct": 50.999230083849845,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "claim": "admitted aggregate gain is below the delay-dependent stability boundary",
      "predicted_Gmax": 32.05554648664719,
      "observed_trained_model_aggregate_gain": 8.582812905311584,
      "observed_active_modules": 8,
      "measured_or_injected_delay": 0.05,
      "predicted_tau_c_at_observed_gain": 0.19797074458180686,
      "within_boundary": true,
      "confirmed": true
    },
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.001,
          "modules": 8,
          "a": 1.0,
          "delay": 0.05
        },
        "result": {
          "mean": 0.0017012821772368625,
          "std": 0.0013511776813881348,
          "per_seed": [
            0.0005999772693030536,
            0.00484928535297513,
            0.0004927608533762395,
            0.0016245391452684999,
            0.0024113263934850693,
            0.0006478673312813044,
            0.0010953845921903849,
            0.0018891164800152183
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.003,
          "modules": 8,
          "a": 1.0,
          "delay": 0.05
        },
        "result": {
          "mean": 0.001572919929458294,
          "std": 0.0011292896441042427,
          "per_seed": [
            0.003213837742805481,
            0.0008874680497683585,
            0.0005741477361880243,
            0.0021032660733908415,
            0.0012076778803020716,
            0.0005505986046019,
            0.003468359587714076,
            0.0005780037608928978
          ],
          "n": 8
        }
      },
      {
        "cfg": {
          "lr": 0.006,
          "modules": 8,
          "a": 1.0,
          "delay": 0.05
        },
        "result": {
          "mean": 0.0026669491053326055,
          "std": 0.0007933035127595409,
          "per_seed": [
            0.0014651163946837187,
            0.0029916735365986824,
            0.003785670967772603,
            0.002830723999068141,
            0.001870379433967173,
            0.003545392770320177,
            0.0018395644146949053,
            0.0030070713255554438
          ],
          "n": 8
        }
      }
    ],
    "protocol": {
      "seeds": [
        0,
        1,
        2,
        3,
        4,
        5,
        6,
        7
      ],
      "sweep_seeds": [
        0,
        1,
        2,
        3
      ],
      "epochs": 12,
      "n_train": 400,
      "n_test": 200
    },
    "structural_match": "dynamics control/stability task with GRU sequence model"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 delay_bench.py",
  "files": [
    "delay_bench.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "Only the registered dynamics track was tested. The latency was injected as 0.05 rather than established from hardware end-to-end deployment, and controller gains were configured once before training rather than recomputed during training. No empirical oscillation boundary sweep across delays or module counts was run.",
  "system_verdict": "partial",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 1,
  "system_judged": true
}