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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Built a structurally matched unordered point-set denoising track and an end-to-end MLP training intervention implementing the Vandermonde repulsion plus second-order fusion correction. Across 8 paired seeds, the best idea configuration had test MSE 0.0849502 versus baseline 0.0717791, paired delta +0.0131711 and permutation p=0.0081, hence a significant loss. The trained-model mechanism signature was also not confirmed: predicted short-gap collision rate increased from 0.0582812 to 0.0653125.",
  "metrics": {
    "baseline": "test MSE mean 0.0717791, std 0.0038503; normalized predicted collision rate 0.0582812; best lr=0.003, weight_decay=0.0001",
    "idea": "test MSE mean 0.0849502, std 0.0036924; normalized predicted collision rate 0.0653125; best lr=0.003, weight_decay=0.0001, lambda=0.1, beta=2, delta=0.08",
    "paired_delta": "idea - baseline = +0.0131711 MSE; 0/8 idea wins; permutation p=0.0081",
    "mechanism_signature": "predicted collision delta +0.00703125; confirmed=false"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 run_bench.py",
  "files": [
    "pointset_fusion_track.py",
    "run_bench.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "The custom benchmark uses 6 one-dimensional points, a compact synthetic denoising distribution, and an MLP rather than a full multi-dimensional diffusion sampler or Sine_beta simulator. It evaluates fixed-noise denoising MSE rather than Wasserstein distance or multi-step generation quality. No larger architectures or point counts were tested.",
  "bench_report": {
    "bench_version": 1,
    "track": "unordered_pointset_denoising",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.003,
        "weight_decay": 0.0001
      },
      "full_mean": 0.07177905738353729,
      "full_std": 0.0038503444468855823,
      "sweep_configs": 6
    },
    "idea": {
      "best_cfg": {
        "lr": 0.003,
        "weight_decay": 0.0001,
        "lam": 0.1,
        "beta": 2.0,
        "delta": 0.08
      },
      "mean": 0.08495018165558577,
      "std": 0.0036923579732418346
    },
    "comparison": {
      "delta_mean": 0.013171124272048473,
      "idea_wins": 0,
      "n_pairs": 8,
      "p_value": 0.0081,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "mechanism_signature": {
      "baseline_predicted_collision": 0.05828124936670065,
      "idea_predicted_collision": 0.06531249871477485,
      "predicted_delta": 0.007031249348074198,
      "confirmed": false
    },
    "custom_track": {
      "name": "unordered_pointset_denoising",
      "file": "pointset_fusion_track.py",
      "domain": "point-set-diffusion"
    }
  },
  "system_verdict": "failed",
  "practical_verdict": "harms",
  "mechanism_ok": 0,
  "system_judged": true
}