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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B.1.526 SARS-CoV-2 Variants Identified in New York City are Neutralized by Vaccine-Elicited and Therapeutic Monoclonal Antibodies
This article has 6 authors:Reviewed by ScreenIT
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The SARS-CoV2 envelope differs from host cells, exposes procoagulant lipids, and is disrupted in vivo by oral rinses
This article has 26 authors:Reviewed by ScreenIT
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SARS-CoV-2 variants B.1.351 and P.1 escape from neutralizing antibodies
This article has 19 authors:Reviewed by ScreenIT
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In vitro inactivation of SARS-CoV-2 with 0.5% povidone iodine nasal spray (Nasodine) at clinically relevant concentrations and timeframes using tissue culture and PCR based assays
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 acquisition and immune pathogenesis among school-aged learners in four diverse schools
This article has 21 authors:Reviewed by ScreenIT
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Value-based pricing of a COVID-19 vaccine
This article has 1 author:Reviewed by ScreenIT
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Escape from neutralizing antibodies by SARS-CoV-2 spike protein variants
This article has 24 authors:Reviewed by ScreenIT
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Homologous and heterologous serological response to the N-terminal domain of SARS-CoV-2
This article has 16 authors:Reviewed by ScreenIT
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Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding
This article has 13 authors:Reviewed by ScreenIT
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An ACE2 Triple Decoy that neutralizes SARS-CoV-2 shows enhanced affinity for virus variants
This article has 16 authors:Reviewed by ScreenIT