{
  "math": {
    "true_alpha": 0.7,
    "fitted_alpha": 0.7,
    "true_beta": 0.62,
    "fitted_beta": 0.6199999999977361,
    "amplitude_abs_error": 0.0,
    "width_abs_error": 2.2638557695131567e-12,
    "rg_L": [
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      1.5,
      2.0,
      3.0
    ],
    "rg_exact_residual": [
      1.7330834682522382e-16,
      1.7643127609576256e-16,
      1.3580559542509378e-16,
      1.9987542215662536e-16
    ],
    "rg_wrong_eta_residual": [
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      0.3061545083459753,
      0.5730789317403018,
      1.0350823782691672
    ],
    "predictions": [
      "log peak amplitude slope equals alpha",
      "log profile width slope equals beta",
      "matched RG rescaling gives zero residual while eta/L does not"
    ]
  },
  "mini_experiment": {
    "device": "cpu",
    "baseline": {
      "accuracy": 1.0,
      "loss": 0.03184313699603081
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    "idea": {
      "accuracy": 0.776,
      "loss": 0.41361381113529205
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    "train_size": 1600,
    "validation_size": 500
  }
}