{
  "model_name": "NNCAM",
  "model_type": "nncam",
  "architectures": ["NNCAM"],
  "framework": "PyTorch",
  "domain": "atmospheric-physics",
  "task": "climate-model-subgrid-parameterization",
  "implementation": {
    "entry_point": "model/nncam.py",
    "scope": "core-method and full-column reduced-sample engineering reproduction",
    "train_script": "scripts/train.py",
    "inference_script": "scripts/inference.py",
    "evaluation_script": "scripts/result.py",
    "synthetic_data_script": "scripts/fake_data.py"
  },
  "architecture": {
    "input_shape": ["B", 94],
    "output_shape": ["B", 65],
    "engineering_depth": 4,
    "engineering_width": 32,
    "paper_depth": 9,
    "paper_width": 256,
    "activation": "LeakyReLU"
  },
  "data": {
    "dataset": "SPCAM aquaplanet simulation",
    "format_version": "1.0",
    "vertical_levels": 30,
    "input_variables": ["T", "Q", "V", "Ps", "Sin", "H", "E"],
    "output_variables": ["dT", "dQ", "SWtoa", "SWsfc", "LWtoa", "LWsfc", "P"],
    "input_layout": "NF",
    "synthetic": true
  },
  "configuration_sources": [
    "conf/config.yaml",
    "model/nncam.py",
    "scripts/fake_data.py",
    "scripts/train.py",
    "scripts/inference.py",
    "scripts/result.py"
  ]
}