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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Discovery and Development of Human SARS-CoV-2 Neutralizing Antibodies using an Unbiased Phage Display Library Approach
This article has 22 authors:Reviewed by ScreenIT
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Mn 2+ coordinates Cap-0-RNA to align substrates for efficient 2′- O -methyl transfer by SARS-CoV-2 nsp16
This article has 9 authors:Reviewed by ScreenIT
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Generation of a Sleeping Beauty transposon-based cellular system for rapid and sensitive identification of SARS-CoV-2 host dependency and restriction factors
This article has 14 authors:Reviewed by ScreenIT
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Quantifying face mask comfort
This article has 9 authors:Reviewed by ScreenIT
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Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial
This article has 37 authors:Reviewed by ScreenIT
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A comparative recombination analysis of human coronaviruses and implications for the SARS-CoV-2 pandemic
This article has 7 authors:Reviewed by ScreenIT
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Relationship between teaching modality and COVID-19, well-being, and teaching satisfaction (campus & corona): A cohort study among students in higher education
This article has 11 authors:Reviewed by ScreenIT
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Impacts of worldwide individual non-pharmaceutical interventions on COVID-19 transmission across waves and space
This article has 17 authors:Reviewed by ScreenIT
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Vaccination boosts protective responses and counters SARS-CoV-2-induced pathogenic memory B cells
This article has 25 authors:Reviewed by ScreenIT
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Fourier spectral density of the coronavirus genome
This article has 1 author:Reviewed by ScreenIT