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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Ionophore antibiotic X-206 is a potent inhibitor of SARS-CoV-2 infection in vitro
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 Neutralizing Antibody Responses Are More Robust in Patients with Severe Disease
This article has 16 authors:Reviewed by ScreenIT
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Calreticulin co-expression supports high level production of a recombinant SARS-CoV-2 spike mimetic in Nicotiana benthamiana
This article has 6 authors:Reviewed by ScreenIT
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Genotypic and antigenic study of SARS-CoV-2 from an Indian isolate
This article has 14 authors:Reviewed by ScreenIT
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Dynamics of the ACE2–SARS-CoV-2/SARS-CoV spike protein interface reveal unique mechanisms
This article has 2 authors:Reviewed by ScreenIT
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A targeted e-learning approach for keeping universities open during the COVID-19 pandemic while reducing student physical interactions
This article has 4 authors:Reviewed by ScreenIT
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Power Laws in Superspreading Events: Evidence from Coronavirus Outbreaks and Implications for SIR Models
This article has 2 authors:Reviewed by ScreenIT
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National Smoking Rates Correlate Inversely with COVID-19 Mortality
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 Spread in India: Dynamics, Modeling, and Future Projections
This article has 1 author:Reviewed by ScreenIT
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Evaluating COVID-19 screening strategies based on serological tests
This article has 5 authors:Reviewed by ScreenIT