{
  "id": "lib-process:materials-science--ml-property-prediction",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "ml-property-prediction",
    "description": "ML Materials Property Prediction - Build and deploy machine learning models for property prediction\nusing descriptors, graph neural networks (CGCNN, MEGNet), or SISSO.",
    "libraryPath": "library/specializations/domains/science/materials-science/ml-property-prediction.js",
    "specialization": "materials-science",
    "references": [
      "- matminer: https://hackingmaterials.lbl.gov/matminer/\n- CGCNN: https://github.com/txie-93/cgcnn\n- MEGNet: https://github.com/materialsvirtuallab/megnet\n- SISSO: https://github.com/rouyang2017/SISSO"
    ],
    "example": "const result = await orchestrate('domains/science/materials-science/ml-property-prediction', {\n  targetProperty: 'band-gap',\n  trainingData: { source: 'materials-project', count: 10000 },\n  modelType: 'cgcnn'\n});",
    "usesAgents": [
      "data-collector",
      "feature-engineer",
      "data-splitter",
      "ml-trainer",
      "model-evaluator",
      "importance-analyst",
      "model-interpreter",
      "model-exporter",
      "technical-writer"
    ]
  },
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    },
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        "weight": 1
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    },
    {
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      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:materials-science--ml-property-prediction",
      "to": "specialization:materials-science",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    },
    {
      "from": "lib-process:materials-science--ml-property-prediction",
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      "kind": "uses_agent",
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}