Confident but unsupported: auditing large language models against supplied evidence boundaries in drug-induced liver injury assessment
- DOI
- 10.3389/fpubh.2026.1904062
- Published
- 2026-08-05
- Container
- Frontiers in Public Health
- Publisher
- Frontiers Media SA
- Open access
- unknown
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uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3389/fpubh.2026.1904062,
title = {Confident but unsupported: auditing large language models against supplied evidence boundaries in drug-induced liver injury assessment},
author = {Jinwan Shi and Yong Ma and Yinhui Liu and Bowen Shi},
year = {2026},
journal = {Frontiers in Public Health},
doi = {10.3389/fpubh.2026.1904062},
url = {https://doi.org/10.3389/fpubh.2026.1904062}
}RIS
TY - JOUR TI - Confident but unsupported: auditing large language models against supplied evidence boundaries in drug-induced liver injury assessment AU - Jinwan Shi AU - Yong Ma AU - Yinhui Liu AU - Bowen Shi PY - 2026 JO - Frontiers in Public Health DO - 10.3389/fpubh.2026.1904062 UR - https://doi.org/10.3389/fpubh.2026.1904062 ER -
APA
Shi, J., Ma, Y., Liu, Y., & Shi, B. (2026). Confident but unsupported: auditing large language models against supplied evidence boundaries in drug-induced liver injury assessment. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2026.1904062
Source records
- crossref · retrieved 2026-11-10T10:27:02.348Z