{
  "id": 22,
  "url": "https://arxiv.org/abs/2607.11084v1",
  "title": "NVAITC AI Scientist: A Governed End-to-End Research System -- A Hypertension GWAS Case Study",
  "summary": "Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond isolated model inference, code generation, or statistical analysis. However, deployment in institutional biomedical environments requires governed mechanisms for research planning, data access, workflow orchestration, evidence tracking, reproducibility, and human oversight. We present NVAITC AI Scientist (NAIS), a governed end-to-end agentic research system designed to support domain-general scie",
  "authors": "Eddie Huang, Ken Liao, Iven Fu, Yang-Hsien Lin, Chao-Shun Zhan, Andy Liao et al.",
  "category": "research",
  "topics": "privacy-surveillance,agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-13T04:53:53.000Z",
  "fetched_at": "2026-07-14T14:14:15.663Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/22",
  "original_url": "https://arxiv.org/abs/2607.11084v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}