This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.
Artificial intelligence。业内人士推荐黑料作为进阶阅读
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海南省白沙黎族自治县医疗集团牙叉社区卫生服务中心副院长韦小丽代表见证了基层医疗条件的巨变——以前很多村没有规范的卫生室，医疗设备只有听诊器、血压计、体温计；如今，标准化村卫生室逐步建成，基层医疗设备不断完善。