Forecasting the publication and citation outcomes of Covid-19 preprints
收藏DataONE2022-09-28 更新2025-05-10 收录
下载链接:
https://search.dataone.org/view/sha256:e5561bec4cf36b9585f8233ccf889ebfd2730e28021e31fb84eb3a9373bf778f
下载链接
链接失效反馈官方服务:
资源简介:
The scientific community reacted quickly to the Covid-19 pandemic in 2020, generating an unprecedented increase in publications. Many of these publications were released on preprint servers such as medRxiv and bioRxiv. It is unknown however how reliable these preprints are, and if they will eventually be published in scientific journals. In this study, we use crowdsourced human forecasts to predict publication outcomes and future citation counts for a sample of 400 preprints with high Altmetric scores. Most of these preprints were published within one year of upload on a preprint server (70%), and 46% of the published preprints appeared in a high-impact journal with a Journal Impact Factor of at least 10. On average, the preprints received 162 citations within the first year. We found that forecasters can predict if preprints will be published after one year and if the publishing journal has high impact. Forecasts are also informative with respect to preprintsâ rankings in terms of Goog...
创建时间:
2025-04-27



