大型语言模型、更新和系统评价自动化工具的评估：第八届国际系统评价自动化协作（ICASR）会议的重要讨论总结。
Large language models, updates, and evaluation of automation tools for systematic reviews: a summary of significant discussions at the eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR).
机构信息
College of Veterinary Medicine, Michigan State University, East Lansing, MI, 48824, USA.
Institute for Evidence-Based Healthcare, Bond University, Robina, QLD, 4226, Australia.
出版信息
Syst Rev. 2024 Nov 27;13(1):290. doi: 10.1186/s13643-024-02666-2.
Abstract
The eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR) was held on September 7 and 8, 2023, at the University College London, London, England. ICASR is an interdisciplinary group whose goal is to maximize the use of technology for conducting rapid, accurate, and efficient evidence synthesis, e.g., systematic reviews, evidence maps, and scoping reviews of scientific evidence. In 2023, the major themes discussed were understanding the benefits and harms of automation tools that have become available in recent years, the advantages and disadvantages of large language models in evidence synthesis, and approaches to ensuring the validity of tools for the proposed task.
摘要
第八届国际系统评价自动化协作会议（ICASR）于 2023 年 9 月 7 日至 8 日在英国伦敦大学学院举行。ICASR 是一个跨学科组织，其目标是最大限度地利用技术进行快速、准确、高效的证据综合，例如系统评价、证据图谱和科学证据的范围综述。2023 年，讨论的主要主题包括了解近年来可用的自动化工具的优缺点、大型语言模型在证据综合中的优缺点，以及确保拟议任务工具有效性的方法。
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