Preprints promote the open and fast communication of non-peer reviewed work. Once a preprint is published in a peer-reviewed venue, the preprint server updates its web page: a prominent hyperlink leading to the newly published work is added. Linking preprints to publications is of utmost importance as it provides readers with the latest version of a now certified work. Yet leading preprint servers fail to identify all existing preprint–publication links. This limitation calls for a more thorough approach to this critical information retrieval task: overlooking published evidence translates into partial and even inaccurate systematic reviews on health-related issues, for instance. We designed an algorithm leveraging the Crossref public and free source of bibliographic metadata to comb the literature for preprint–publication links. We tested it on a reference preprint set identified and curated for a living systematic review on interventions for preventing and treating COVID-19 performed by international collaboration: the COVID-NMA initiative (covid-nma.com). The reference set comprised 343 preprints, 121 of which appeared as a publication in a peer-reviewed journal. While the preprint servers identified 39.7% of the preprint–publication links, our linker identified 90.9% of the expected links with no clues taken from the preprint servers. The accuracy of the proposed linker is 91.5% on this reference set, with 90.9% sensitivity and 91.9% specificity. This is a 16.26% increase in accuracy compared to that of preprint servers. We release this software as supplementary material to foster its integration into preprint servers’ workflows and enhance a daily preprint–publication chase that is useful to all readers, including systematic reviewers. This preprint–publication linker currently provides day-to-day updates to the biomedical experts of the COVID-NMA initiative.

预印本促进了非同行评审工作的开放和快速交流。一旦预印本在同行评审的场所发布，预印本服务器就会更新其网页：添加一个指向新发布作品的显着超链接。将预印本与出版物联系起来至关重要，因为它为读者提供了现已获得认证的作品的最新版本。然而，领先的预印本服务器无法识别所有现有的预印本-出版链接。这种限制要求对这一关键信息检索任务采取更彻底的方法：例如，忽视已发表的证据会转化为对健康相关问题的部分甚至不准确的系统评价。我们设计了一种算法，利用 Crossref 公共和免费的书目元数据来源来梳理文献以获得预印本-出版链接。我们在一个参考预印本集上对其进行了测试，该预印本集为国际合作开展的 COVID-19 预防和治疗干预措施进行了实时系统评价：COVID-NMA 倡议 (covid-nma.com)。参考集包括 343 个预印本，其中 121 个作为出版物出现在同行评审期刊上。虽然预印本服务器识别了 39.7% 的预印本-出版链接，但我们的链接器识别了 90.9% 的预期链接，但没有从预印本服务器中获取任何线索。在这个参考集上，所提出的链接器的准确度为 91.5%，灵敏度为 90.9%，特异性为 91.9%。与预印本服务器相比，准确度提高了 16.26%。我们将此软件作为补充材料发布，以促进其与预印本服务器工作流程的集成，并增强对所有读者（包括系统审稿人）有用的每日预印本出版追逐。该预印本-出版物链接器目前为 COVID-NMA 倡议的生物医学专家提供日常更新。