ScreenIT
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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Negative attitudes about facemasks during the COVID-19 pandemic: The dual importance of perceived ineffectiveness and psychological reactance
This article has 2 authors:Reviewed by ScreenIT
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The DEAD box RNA helicase DDX42 is an intrinsic inhibitor of positive‐strand RNA viruses
This article has 26 authors:Reviewed by Review Commons, ScreenIT
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Multisystem inflammatory syndrome in children (MIS-C) temporally associated with SARS-CoV-2 infection: a scoping review of the literature
This article has 9 authors:Reviewed by ScreenIT
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Risk Assessment of COVID-19 Airborne Infection During Hybrid Learning
This article has 3 authors:Reviewed by ScreenIT
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HAS COUNTRYWIDE LOCKDOWN WORKED AS A FEASIBLE MEASURE IN BENDING THE COVID-19 CURVE IN DEVELOPING COUNTRIES?
This article has 2 authors:Reviewed by ScreenIT
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TRIM28 regulates SARS-CoV-2 cell entry by targeting ACE2
This article has 9 authors:Reviewed by ScreenIT
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Brief Report: High-Quality Masks Can Reduce Infections and Deaths in the US
This article has 6 authors:Reviewed by ScreenIT
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The airborne contagiousness of respiratory viruses: A comparative analysis and implications for mitigation
This article has 4 authors:Reviewed by ScreenIT
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Analyzing the vast coronavirus literature with CoronaCentral
This article has 2 authors:Reviewed by ScreenIT
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Natural SARS-CoV-2 Infection in Kept Ferrets, Spain
This article has 9 authors:Reviewed by ScreenIT