Before revision:  SVM and RF achieved macro-averaged F1 scores of 0.45 and 0.6 while BERT_{base} and BERT_{rad} achieved 0.61 and 0.63. Knowledge distillation improved overall performance on the minority classes, achieving a F1 score of 0.66 . Additionally, by choosing the optimal threshold, the BERT models could classify over 50\% of test samples within 5\% error rate and potentially alleviate half of radiologist protocoling workload .
After revision:  SVM and RF achieved macro-averaged F1 scores of 0.45 and 0.6 while BERT_{base} and BERT_{rad} achieved 0.61 and 0.63. Knowledge distillation improved overall performance on the minority classes, achieving a F1 score of 0.66 .