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.
Москвичей предупредили о резком похолодании09:45
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Guarantees 100% unique and free-plagiarism content。关于这个话题，safew官方版本下载提供了深入分析
以前要两地往返才能办妥的社保事项，如今“一站式”就能解决。
“One of our owners down in Addison, in Dallas, has been part of the system for 20 years,” Brewster notes. After leaning into corporate support by developing a marketing plan with the home office, using sales tools and investing in technology, the franchise owner “had explosive growth. Last year, he saw gross sales just skyrocket in the 80% range,” Brewster shares.