{"ok":true,"nota":{"id":"aff3953253ff7a90","slug":"cada-vez-mas-resumenes-de-revistas-medicas-parecen-escritos-por-inteli-aff395","titulo":"Cada vez más resúmenes de revistas médicas parecen escritos por inteligencia artificial","resumen":"Investigadores revisaron resúmenes de 12 revistas de medicina entre 2020 y 2026 con un detector de texto generado por IA. La proporción de textos marcados como artificiales creció con el tiempo, aunque varía mucho según la revista.","fuente":"medrxiv","fuenteNombre":"medRxiv · preprints","color":"#1f7a4d","autor":"Flanders, M. D., Caunca, M., Mehrotra, A., Ackley, S. F.","url":"https://www.medrxiv.org/content/10.64898/2026.10.24.26366055v1?rss=1","imagen":"/hoy/portada/aff3953253ff7a90","tema":"ciencia","subtemas":["inteligencia artificial","publicaciones científicas","medicina","integridad académica","revistas médicas"],"entidades":["medRxiv","GPTZero"],"formato":"dato","entretenimiento":false,"pubTs":"2026-10-26T00:00:00.000Z","indexTs":"2026-10-26T14:53:25.658Z","hash":"7fc4157fd82ec846ba899a383fc6a0868413ebfa13434e4a744b5f3068664e61","tsa":{"time":"Oct 26 14:54:15 2026 GMT","provider":"freetsa.org","sobre":"sello"},"stats":{"views":0,"likes":0,"clicks":0,"dwell":0},"tipo":"normal","registro":"hallazgo","porQueImporta":"Los resúmenes son lo primero que lee un médico, un paciente o un periodista antes de decidir si confía en un estudio. Si una parte del texto sale de una máquina sin revisión suficiente, cuesta más saber qué fue verificado por personas. El dato más fuerte es que la diferencia entre revistas es enorme, así que no se puede dar por sentado el mismo nivel de control en todas. Los detectores tampoco son infalibles, y eso obliga a leer con más cuidado lo que se publica.","quienFirma":"medRxiv (preprint, sin revisión por pares)","confianza":"preprint","consulta":null},"sello":{"hash":"7fc4157fd82ec846ba899a383fc6a0868413ebfa13434e4a744b5f3068664e61","sello":"fe3e9dea98033f6a0e7d7ba5bba4e9e733a7ce23c08a260e44680b9a8143cc94","beacon":{"drand":{"cadena":"8990e7a9aaed2ffed73dbd7092123d6f289930540d7651336225dc172e51b2ce","ronda":6586513,"aleatorio":"29252d64ae5579343d3b4c7195e7f25e20e7efda9f7d116c213bca78231653a8","tiempo":"2026-10-26T14:53:30.000Z"},"nist":{"cadena":2,"pulso":2000450,"salida":"EA784D98D5763B66F010C392D53318D62D88381D9414E0DC9F82D155C4472FF568C7FE97610A1FBF61DB527240CD9D1CBCAD8004F69E7935CD2BA4DAEF79B485","tiempo":"2026-10-26T14:53:00.000Z"},"noAntes":"2026-10-26T14:53:30.000Z"},"verificacion":{"drand":true,"nist":true},"tsa":{"time":"Oct 26 14:54:15 2026 GMT","provider":"freetsa.org","sobre":"sello"},"original":{"titulo":"AI-Assisted Writing Across Medical Journals: Heterogeneity in Prevalence and Trends","descripcion":"Background: Estimates of generative artificial intelligence (AI) use in the medical literature vary widely, potentially reflecting differences across journals. We estimated changes in the prevalence of AI-generated writing over time using abstracts from 12 general medical journals. Methods: We randomly sampled up to 200 abstracts per journal-year from publications dated January 1, 2020, through August 8, 2026. Abstracts were scored using GPTZero, with journal-specific thresholds calibrated to fix a 1% false-positive rate (FPR) in the pre-AI baseline period (2020-2021). We estimated annual detector-positive proportions and calculated a publication-volume-weighted estimate across sampled journ","pubDate":"2026-10-26","url":"https://www.medrxiv.org/content/10.64898/2026.10.24.26366055v1?rss=1"},"indexado":"2026-10-26T14:53:25.658Z"}}