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AIO requires understanding how language models decide which sources to reference when answering questions. These models don't follow the same rules as search engine algorithms. They're not counting backlinks or analyzing page load speed. They're evaluating whether content provides clear, accurate, comprehensive answers to questions people actually ask. They're assessing credibility through different signals than traditional search engines use. They're making probabilistic decisions about which information best satisfies a query based on patterns learned during training and information retrieved during real-time web searches.

If you are familiar with SMT-LIB you may notice that both the re.from_ecma2020 function and the single-quote string notation ('regex') are nonstandard additions in Ostrich. That's because the regexes in SMT-LIB are textbook regexes without most of the features of full perl-compatible regular expressions, and because they end up needing a lot of escaping in practical use, some of which is nontrivial.

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