ClarusC64/clinical-fragility-amplification-detection-v0.1

from dataclasses import dataclass from typing import Dict, Any, List @dataclass class ScoreResult: score: float details: Dict[str, Any] def score(sample: Dict[str, Any], prediction: str) -> ScoreResult: p = (prediction or "").lower() words_ok = len(p.split()) <= 520 has_index = "fragility" in p and "index" in p has_triggers = "trigger" in p or "missed" in p or "dose" in p has_rebound = "rebound" in p or "withdraw" in p has_range = "operating" in p or "narrow" in p… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-fragility-amplification-detection-v0.1.