{
  "project": "FEMSurrogateTutorial",
  "phase": "2-dataset-and-surrogates",
  "steps": [
    {
      "step": 0,
      "name": "sampling-and-dataset",
      "status": "completed",
      "summary": "Added reproducible LHS sampling, BeamParameters/AnalysisResult schema, and Beam2D dataset builder using the in-repository solver."
    },
    {
      "step": 1,
      "name": "surrogate-common",
      "status": "completed",
      "summary": "Added reproducible dataset split helper, evaluation result dataclasses, regression metrics, fit/predict timing, and prediction table generation."
    },
    {
      "step": 2,
      "name": "surrogate-models",
      "status": "completed",
      "summary": "Added scikit-learn builders and registry for RSM, GPR, Random Forest, Gradient Boosting, and MLP models."
    },
    {
      "step": 3,
      "name": "plotting-and-results",
      "status": "completed",
      "summary": "Added parity and residual diagnostic plots, metrics table creation, and metric comparison plot helpers returning matplotlib figures."
    }
  ]
}