A pipeline combining BioBERT sentiment, a stress lexicon, and topic models reports F1=0.84 for burnout detection, but the labels are derived from the same narrative features used as inputs, making the result circular.
Intensive care unit burnout: A systematic review,
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A Narrative-Driven Computational Framework for Clinician Burnout Surveillance
A pipeline combining BioBERT sentiment, a stress lexicon, and topic models reports F1=0.84 for burnout detection, but the labels are derived from the same narrative features used as inputs, making the result circular.