Table 4.

Classifier Performances for the Model Generalizability Analysis Experiments

Model	Precision/PPV	Recall/sensitivity	F 1 score	95% CI
Training on AHS and testing on PHS
RoBERTa	0.96	0.83	0.89	0.87–0.91
SVM	0.99	0.79	0.88	0.86–0.90
Training on PHS and testing on AHS
RoBERTa	0.84	0.83	0.83	0.79–0.87
SVM	0.74	0.95	0.83	0.79–0.87

The metrics are precision, recall, and F ₁ score for the positive class. For RoBERTa, the sliding window setting described in the article is used. The 95% CIs were computed via bootstrap resampling. AHS indicates adult health care system; PHS, pediatric health care system; PPV, positive predictive value; RoBERTa, a robustly optimized transformer‐based model for language understanding; and SVM, support vector machine.