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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Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell epitope mapping
This article has 25 authors:Reviewed by ScreenIT
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Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19
This article has 69 authors:Reviewed by ScreenIT
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Potent Neutralization of SARS-CoV-2 by Hetero-Bivalent Alpaca Nanobodies Targeting the Spike Receptor-Binding Domain
This article has 15 authors:Reviewed by ScreenIT
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Simultaneous evaluation of antibodies that inhibit SARS-CoV-2 variants via multiplex assay
This article has 21 authors:Reviewed by ScreenIT
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Distinct spatial arrangements of ACE2 and TMPRSS2 expression in Syrian hamster lung lobes dictates SARS-CoV-2 infection patterns
This article has 14 authors:Reviewed by ScreenIT
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Increased complement activation is a distinctive feature of severe SARS-CoV-2 infection
This article has 31 authors:Reviewed by ScreenIT
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Reopening schools in a context of low COVID-19 contagion: consequences for teachers, students and their parents
This article has 3 authors:Reviewed by ScreenIT
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Dynamic versus Continuous Interventions: Optimizing Lockdown Policies for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Detection of Mutations Associated with Variants of Concern Via High Throughput Sequencing of SARS-CoV-2 Isolated from NYC Wastewater
This article has 11 authors:Reviewed by ScreenIT
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The Impact of Keeping Indoor Dining Closed on COVID-19 Rates Among Large US Cities
This article has 9 authors:Reviewed by ScreenIT