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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Establishment of human post-vaccination SARS-CoV-2 standard reference sera
This article has 18 authors:Reviewed by ScreenIT
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COVID-19 vaccination elicits an evolving, cross-reactive antibody response to epitopes conserved with endemic coronavirus spike proteins
This article has 24 authors:Reviewed by ScreenIT
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Detection of SARS‐CoV‐2 in different human biofluids using the loop‐mediated isothermal amplification assay: A prospective diagnostic study in Fortaleza, Brazil
This article has 18 authors:Reviewed by ScreenIT
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The N764K and N856K mutations in SARS-CoV-2 Omicron BA.1 S protein generate potential cleavage sites for SKI-1/S1P protease
This article has 1 author:Reviewed by ScreenIT
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Death review caused by Covid 19 in Bangladesh
This article has 3 authors:Reviewed by ScreenIT
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Bacteriophage-Derived Double-Stranded RNA Exerts Anti-SARS-CoV-2 Activity In Vitro and in Golden Syrian Hamsters In Vivo
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron variant virus isolates are highly sensitive to interferon treatment
This article has 6 authors:Reviewed by ScreenIT
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Values and preferences of the general population in Indonesia in relation to rapid COVID‐19 antigen self‐tests: A cross‐sectional survey
This article has 8 authors:Reviewed by ScreenIT
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Forecasted Trends of the New COVID-19 Epidemic Due to the Omicron Variant in Thailand, 2022
This article has 5 authors:Reviewed by ScreenIT
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Are allergic diseases a risk factor for systemic side effects after COVID-19 vaccines?
This article has 2 authors:Reviewed by ScreenIT