作者对Tiffet等人关于“命名实体识别中大型语言模型的性能和可重复性：在受控环境中使用的考虑”的评论的回应。

IF 3.8 2区医学 Q1 PHARMACOLOGY & PHARMACY

Drug Safety Pub Date : 2025-09-02 DOI:10.1007/s40264-025-01590-1

Juergen Dietrich, André Hollstein

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Authors' response to Tiffet et al.'s comment on "Performance and Reproducibility of Large Language Models in Named Entity Recognition: Considerations for the Use in Controlled Environments".

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来源期刊

Drug Safety 医学-毒理学

CiteScore

7.60

自引率

7.10%

发文量

112

审稿时长

6-12 weeks

期刊介绍： Drug Safety is the official journal of the International Society of Pharmacovigilance. The journal includes: Overviews of contentious or emerging issues. Comprehensive narrative reviews that provide an authoritative source of information on epidemiology, clinical features, prevention and management of adverse effects of individual drugs and drug classes. In-depth benefit-risk assessment of adverse effect and efficacy data for a drug in a defined therapeutic area. Systematic reviews (with or without meta-analyses) that collate empirical evidence to answer a specific research question, using explicit, systematic methods as outlined by the PRISMA statement. Original research articles reporting the results of well-designed studies in disciplines such as pharmacoepidemiology, pharmacovigilance, pharmacology and toxicology, and pharmacogenomics. Editorials and commentaries on topical issues. Additional digital features (including animated abstracts, video abstracts, slide decks, audio slides, instructional videos, infographics, podcasts and animations) can be published with articles; these are designed to increase the visibility, readership and educational value of the journal’s content. In addition, articles published in Drug Safety Drugs may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand important medical advances.