Large language models as internal consistency checkers for ophthalmic manuscripts

Large language models (LLMs) are increasingly used in scientific writing, while their potential application to editorial assessment and peer review has attracted growing interest [ 1 , 2 , 3 ]. However, their ability to identify internal inconsistencies within scientific manuscripts remains poorly characterised. We evaluated four contemporary LLMs as automated consistency checkers using published ophthalmic literature.