How the monitored publications were assessed

Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.

9 items read as adverse

• Being judged through the record: A Rosenhan-inspired test of psychiatric label sensitivity in large language models
  -63 arXiv cs.CY (Computers and Society) 12d ago low agreement · ±70
• AI doctors’ orders come with a sky-high bill
  -59 Nature 2026-10-21 low agreement · ±60
• Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?
  -50 arXiv cs.AI 2026-10-21 single model
• Automated screening of privacy risks in medical AI
  -43 arXiv cs.LG (Machine Learning) 2026-10-23 low agreement · ±165
• Risk and Refusal: Mechanisms of LLM Responses to Suicidal Ideation
  -43 arXiv cs.CY (Computers and Society) 2026-10-19 low agreement · ±115
• Researchers use AI to design proteins that cut up other proteins
  -42 Ars Technica: AI 2026-10-14 low agreement · ±175
• British households would be £5,000 richer if we were more innovative. Let’s unleash our talents | Gordon Brown
  -33 The Guardian: Artificial Intelligence 2026-10-09 low agreement · ±170
• Matched but Not Better: An Equivalence-Tested Benchmark of Quantum Machine Learning on Six Clinical Datasets and the QML-Health-READY Reporting Framework
  -25 arXiv cs.LG (Machine Learning) 3d ago single model
• AusClinBench: a deterministically scored benchmark of large language models against current Australian clinical policy
  -21 arXiv cs.CY (Computers and Society) 13d ago low agreement · ±165

Across the whole window

The two tables below describe every item in the last 30 days under medicine. They are deliberately not narrowed by the reading filter (currently adverse), because a mean taken only over items already selected for their score would just restate the filter.

By topic

By source

A source's mean says how the items it published were read. It is not a rating of the source.