{
  "id": 16558281,
  "title": "Bayesian Stacking of Quantitative Adverse Outcome Pathways Isolates Primary Drivers of Liver Steatosis",
  "url": "https://urgent.news/2026/10/25/bayesian-stacking-of-quantitative-adverse-outcome-pathways-isolates",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-25T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.20.760409v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "The quantification of adverse outcome pathways (qAOPs) involving multiple converging pathways remains a fundamental challenge in toxicology. This difficulty is worsened by small in vitro datasets with missing values and heteroscedasticity, which limit the estimation of non-linear response functions and the robust estimation of uncertainty. To overcome these limitations, we developed a framework…",
  "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."
}