Published January 2021
| public
Journal Article
Automated screening of COVID-19 preprints: can we help authors to improve transparency and reproducibility?
Abstract
The COVID-19 pandemic has thrust preprints into the spotlight, attracting attention from the media and the public, as well as from scientists. Preprints are articles not yet published in a peer-reviewed journal, and as such they offer a unique opportunity to improve reporting. The Automated Screening Working Group (https://scicrunch.org/ASWG/about/COVIDPreprint) aims to provide rapid feedback that may help authors of COVID-19 preprints to improve their transparency and reproducibility.
Additional Information
© 2021 Nature Publishing Group. Published 11 January 2021. SciScore was funded by the US National Institutes of Health (OD024432, DA039832, DK097771, MH119094, and HHSN276201700124P). The development and application of Seek & Blastn is supported by grants from the US Office of Research Integrity, grant ID ORIIR180038-01-00 (J.A.B., C.L.), and from the National Health and Medical Research Council of Australia, Ideas grant ID APP1184263 (J.A.B., C.L., A.C.D.). Development of Limitation-Recognizer was partially supported by the intramural research program of the NIH and National Library of Medicine. Competing interests: A.B. is a cofounder of SciCrunch Inc.Additional details
- Eprint ID
- 107532
- DOI
- 10.1038/s41591-020-01203-7
- Resolver ID
- CaltechAUTHORS:20210119-072728244
- OD024432
- NIH
- DA039832
- NIH
- DK097771
- NIH
- MH119094
- NIH
- HHSN276201700124P
- NIH
- ORIIR180038-01-00
- Department of Health and Human Services
- APP1184263
- National Health and Medical Research Council of Australia
- Created
-
2021-01-19Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field
- Caltech groups
- COVID-19