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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "The registered built-in sequence track was rerun end-to-end with matched transformer systems, an 8-seed paired protocol, tuned baseline learning-rate sweep, and a three-setting idea rank sweep. The dyadic system slightly improved mean test MSE, but the paired permutation test was non-significant, so there is no demonstrated benchmark win. The trained-model mechanism signature was confirmed quantitatively: observed rank 4 <= predicted bound 5 and observed relative cross-output error 3.26e-05 <= 1e-3.",
  "metrics": {
    "baseline": "sequence/transformer_tiny, tuned lr=0.001; 8-seed mean test MSE=0.3629476018, std=0.0543452814.",
    "idea": "rank=4 at shared lr=0.001; 8-seed mean test MSE=0.3599541374, std=0.0551822606; paired delta=-0.0029934645, 5/8 wins, permutation p=0.53235."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "sequence",
    "model": "transformer_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.001,
        "temperature": 1.0
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "temperature": 1.0
          },
          "mean": 0.34783465415239334
        },
        {
          "cfg": {
            "lr": 0.003,
            "temperature": 1.0
          },
          "mean": 0.3491433709859848
        },
        {
          "cfg": {
            "lr": 0.005,
            "temperature": 1.0
          },
          "mean": 0.40824612975120544
        }
      ],
      "full": {
        "mean": 0.36294760182499886,
        "std": 0.054345281417173805,
        "per_seed": [
          0.39175504446029663,
          0.3038984537124634,
          0.30141177773475647,
          0.3942733407020569,
          0.35095956921577454,
          0.3010490834712982,
          0.4579026699066162,
          0.4023308753967285
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.3599541373550892,
      "std": 0.05518226062931197,
      "per_seed": [
        0.3880409896373749,
        0.2888491451740265,
        0.32456186413764954,
        0.3811890184879303,
        0.3370722830295563,
        0.29420310258865356,
        0.4586992561817169,
        0.40701743960380554
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": -0.002993464469909668,
      "idea_wins": 5,
      "n_pairs": 8,
      "per_seed_diffs": [
        -0.003714054822921753,
        -0.01504930853843689,
        0.023150086402893066,
        -0.013084322214126587,
        -0.013887286186218262,
        -0.006845980882644653,
        0.000796586275100708,
        0.004686564207077026
      ],
      "p_value": 0.53235,
      "mde": 0.010661430606466927,
      "mde_rel_pct": 2.9374572397939445,
      "verdict": "no measurable effect",
      "system_worked": false
    },
    "mechanism_signature": {
      "epsilon": 0.001,
      "predicted_rank_bound": 5,
      "observed_rank": 4,
      "trained_model_cross_output_relative_error": 3.261449819547124e-05,
      "predicted_error_bound": 0.001,
      "confirmed": true
    },
    "protocol_notes": {
      "paired_seeds": [
        0,
        1,
        2,
        3,
        4,
        5,
        6,
        7
      ],
      "epochs": 20,
      "architecture_difference_only": "dense self-attention versus within-side dense attention plus cached dyadic Hankel cross-boundary branch"
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py",
  "files": [
    "stage2_bench.py",
    "bench_report.json"
  ],
  "limitations": "Only the registered sequence forecast track was tested at window length 32, 400 training samples, 200 test samples, and 20 epochs. Wall-clock speed, FLOPs, KV-cache memory, longer contexts, multiple dyadic scales, learned gates, causal masking, and language-model perplexity were not measured.",
  "system_verdict": "partial",
  "practical_verdict": "no_effect",
  "mechanism_ok": 1,
  "system_judged": true
}