Forecasting the publication and citation outcomes of COVID-19 preprints.

ABSTRACT: Many publications on COVID-19 were released on preprint servers such as medRxiv and bioRxiv. It is unknown how reliable these preprints are, and which ones 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 score. Most of these preprints were published within 1 year of upload on a preprint server (70%), with a considerable fraction (45%) appearing 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 1 year and if the publishing journal has high impa

SUBMITTER: Gordon M 

PROVIDER: S-EPMC9515639 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature