{
  "framework": "PyTorch/NumPy/scikit-learn",
  "task": "causal-network-evaluation-and-precipitation-constraint",
  "model": "CausalModelEvaluation",
  "input_format": "T50 or BT50",
  "output_format": "source-target-lag tensors [50,50,10]",
  "protocol": "lagged conditional regression approximation to linear PCMCI plus asymmetric signed F1, Taylor S-score, and RBF+white GP",
  "default_config": "conf/config.yaml",
  "training": "scripts/train.py",
  "inference": "scripts/inference.py",
  "evaluation": "scripts/result.py",
  "visualization": "scripts/result.py"
}