Tag
B-CARE is a prediction-blind framework that uses a fixed LLM verifier to assign classwise evidence scores for ranking potentially incorrect stance predictions, achieving a mean AUROC of 0.735 across 12 dataset-model settings and capturing 41% of errors within the top 20% highest-risk predictions.