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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Unraveling the molecular basis of host cell receptor usage in SARS-CoV-2 and other human pathogenic β-CoVs
This article has 4 authors:Reviewed by ScreenIT
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Racial and Ethnic Disparities in Population-Level Covid-19 Mortality
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 NSP1 C-terminal (residues 131–180) is an intrinsically disordered region in isolation
This article has 5 authors:Reviewed by ScreenIT
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Epidemic Analysis of COVID-19 in Egypt, Qatar and Saudi Arabia using the Generalized SEIR Model
This article has 3 authors:Reviewed by ScreenIT
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Features of α-Hydroxybutyrate Dehydrogenase during various specific periods in COVID-19 patients within Xiangyang, China: a cohort study
This article has 8 authors:Reviewed by ScreenIT
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Rapid Inactivation of SARS-CoV-2 with Ozonated Water
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 control on a large urban college campus without mass testing
This article has 36 authors:Reviewed by ScreenIT
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Biostatistical Investigation of Correlation Between COVID-19 and Diabetes Mellitus
This article has 8 authors:Reviewed by ScreenIT
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Superspreading as a Regular Factor of the COVID-19 Pandemic: II. Quarantine Measures and the Second Wave
This article has 1 author:Reviewed by ScreenIT
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Rapidly self-sterilizing PPE capable of 99.9% SARS-CoV-2 deactivation in 30 seconds
This article has 15 authors:Reviewed by ScreenIT