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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Changes in Eating Habits and Sedentary Behavior During the COVID-19 Pandemic in Adolescents With Chronic Conditions
This article has 19 authors:Reviewed by ScreenIT
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FRONTLINE COMMUNITIES AND SARS-COV-2 - MULTI-POPULATION MODELING WITH AN ASSESSMENT OF DISPARITY BY RACE/ETHNICITY USING ENSEMBLE DATA ASSIMILATION
This article has 7 authors:Reviewed by ScreenIT
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Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of nsp14/nsp10 exoribonuclease
This article has 19 authors:Reviewed by ScreenIT
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The Impact of Real-Time Whole-Genome Sequencing in Controlling Healthcare-Associated SARS-CoV-2 Outbreaks
This article has 14 authors:Reviewed by ScreenIT
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Multi-level inhibition of coronavirus replication by chemical ER stress
This article has 17 authors:Reviewed by ScreenIT
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The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation
This article has 16 authors:Reviewed by ScreenIT
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Membrane lectins enhance SARS-CoV-2 infection and influence the neutralizing activity of different classes of antibodies
This article has 22 authors:Reviewed by ScreenIT
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A realistic transfer method reveals low risk of SARS-CoV-2 transmission via contaminated euro coins and banknotes
This article has 18 authors:Reviewed by ScreenIT
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Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts
This article has 8 authors:Reviewed by ScreenIT
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Rapid and Efficient Inactivation of SARS-CoV-2 from Surfaces using UVC Light Emitting Diode Device
This article has 8 authors:Reviewed by ScreenIT