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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mRNA vaccination boosts cross-variant neutralizing antibodies elicited by SARS-CoV-2 infection
This article has 19 authors: -
Comprehensive Comparison of RNA-Seq Data of SARS-CoV-2, SARS-CoV and MERS-CoV Infections: Alternative Entry Routes and Innate Immune Responses
This article has 7 authors:Reviewed by ScreenIT
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The D614G mutation redirects SARS-CoV-2 spike to lysosomes and suppresses deleterious traits of the furin cleavage site insertion mutation
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 CG: Tracking SARS-CoV-2 mutations by locations and dates of interest
This article has 5 authors:Reviewed by ScreenIT
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Lockdown fatigue among college students during the COVID‐19 pandemic: Predictive role of personal resilience, coping behaviors, and health
This article has 2 authors:Reviewed by ScreenIT
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Impact of tocilizumab administration on mortality in severe COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Population based estimates of comorbidities affecting risk for complications from COVID-19 in the US
This article has 3 authors:Reviewed by ScreenIT
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Epidemiologial Analysis of Patients Presenting to a West London District General Hospital Requiring Admission with Covid-19
This article has 4 authors:Reviewed by ScreenIT
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Early estimates of COVID-19 infections in small, medium and large population clusters
This article has 8 authors:Reviewed by ScreenIT
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A comprehensive antigen production and characterisation study for easy-to-implement, specific and quantitative SARS-CoV-2 serotests
This article has 58 authors:Reviewed by ScreenIT