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.
"As a GP I see women wait months and months and months to see gynae [specialists] because obviously the secondary care service has to prioritise suspected cancer cases.
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And then argues that the answer is that LLMs are not good enough yet. They can do 90% of the work, so there’s still a substantial amount of manual polish, and thus, increased costs.，推荐阅读同城约会获取更多信息