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Model Retirement Creates Reproducibility Risk in Biomedical AI Publications — arXiv:2609.04699

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.04699
License (as archived): CC0-1.0
Archived: 2026-10-16T22:20:51.196Z
SHA-256 of the archived text: 06432f3ab62a6bee0b37a48b731f52f38619bb02c72b333cc31b2171db6bda4a
Stable URL of this page: https://metraipolis.com/documento/dc_6147a67b9803

How to cite

Model Retirement Creates Reproducibility Risk in Biomedical AI Publications — arXiv:2609.04699 — arXiv (en), https://arxiv.org/abs/2609.04699 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_6147a67b9803 (Metraipolis archive dc_6147a67b9803, sha256 06432f3ab62a6bee0b37a48b731f52f38619bb02c72b333cc31b2171db6bda4a)

BibTeX

@misc{dc6147a67b9803,
  title = {Model Retirement Creates Reproducibility Risk in Biomedical AI Publications — arXiv:2609.04699},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.04699},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_6147a67b9803; sha256 06432f3ab62a6bee0b37a48b731f52f38619bb02c72b333cc31b2171db6bda4a},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.04699. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Background. Large language models (LLMs) are being adopted in biomedical research at a rapid and accelerating pace, yet commercial services that host many widely used models operate under deprecation schedules that can complicate scientific reproducibility. Methods. We searched PubMed for original research articles from 2022 through March 2026 that applied a specific LLM to a biomedical task. An extraction agent identified model names from 61,077 article abstracts with human reviewers validating a subset for extraction accuracy. Extracted model names were normalized to canonical model identifiers. Lifecycle data (release date, retirement date, status) were compiled for the 50 most frequently used models. Results. We identified 8,931 paper-model mentions spanning 5,242 unique publications after restricting the analysis to the 50 most frequently used models. Among these mentions, 77.7% cited a commercial closed-weight model. Overall, 42% involved a model that was already retired by the time of official publication or is scheduled to retire within two years of publication. The median interval from publication to model retirement was 538 days. Conclusion. Many biomedical publications using LLMs are on a trajectory toward computational non-reproducibility after publication. Model deprecation should be treated as a core reporting and preservation issue for biomedical research.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-07 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2609.04699 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T22:18:11.380Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-07?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).