{
  "id": 9704121,
  "title": "AI Models Excel at Orchestration but Falter at Biological Judgment: Findings from an Agentic Gene Annotation Study",
  "url": "https://urgent.news/2026/09/24/ai-models-excel-at-orchestration-but-falter-at-biological-judgment",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-24T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.23.753765v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large language model (LLM) agents are increasingly used both to direct biological analyses and to interpret their results. The core functions of agents-workflow control and biological adjudication-are often combined within the same agent and evaluated end-to-end, making it difficult to determine whether a model that is useful in one role is also reliable in the other. In this study, Genome…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}