it seems like a little more automation could make an ATM part of the system.
人 民 网 版 权 所 有 ，未 经 书 面 授 权 禁 止 使 用
，详情可参考搜狗输入法下载
"Aside from the personal toll on people with arthritis, the stakes are high for government who have an uphill challenge to bring down waiting lists to meet ambitious targets."
나경원 “당이 제대로 싸우지 못하는 현실 참담”。业内人士推荐爱思助手下载最新版本作为进阶阅读
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.
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