The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Narrative Analysis of Childbearing Experiences During the COVID-19 Pandemic
This article has 6 authors:Reviewed by ScreenIT
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Hospital load and increased COVID-19 related mortality in Israel
This article has 9 authors:Reviewed by ScreenIT
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Mental health among pregnant women during the pandemic in Sweden– a mixed methods approach using data from the Mom2B mobile application for research
This article has 9 authors:Reviewed by ScreenIT
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A scalable saliva-based, extraction-free rt-lamp protocol for sars-cov-2 diagnosis
This article has 20 authors:Reviewed by ScreenIT
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Knowledge, Attitudes, and Practices Regarding COVID-19 Among Health Care Workers in Public Health Facilities in Eastern Ethiopia: Cross-sectional Survey Study
This article has 9 authors:Reviewed by ScreenIT
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Direct Simulation of the CoVid-19 epidemic
This article has 3 authors:Reviewed by ScreenIT
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Phylogenomics reveals multiple introductions and early spread of SARS‐CoV‐2 into Peru
This article has 7 authors:Reviewed by ScreenIT
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Vapur: A Search Engine to Find Related Protein - Compound Pairs in COVID-19 Literature
This article has 5 authors:Reviewed by ScreenIT
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Extremely Preterm Infant Admissions Within the SafeBoosC-III Consortium During the COVID-19 Lockdown
This article has 49 authors:Reviewed by ScreenIT
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High-Frequency Self-Testing by Schoolteachers for Sars-Cov-2 Using a Rapid Antigen Test: Results of the Safe School Hesse study
This article has 8 authors:Reviewed by ScreenIT