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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A method for the generation of pseudotyped virus particles bearing SARS coronavirus spike protein in high yields
This article has 8 authors:Reviewed by ScreenIT
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Age-specific rate of severe and critical SARS-CoV-2 infections estimated with multi-country seroprevalence studies
This article has 2 authors:Reviewed by ScreenIT
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Outbreak of P.3 (Theta) SARS-CoV-2 emerging variant of concern among service workers in Louisiana
This article has 4 authors:Reviewed by ScreenIT
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Mental health of HBCU college students during the COVID-19 pandemic
This article has 2 authors:Reviewed by ScreenIT
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Willingness to receive vaccination against COVID-19: results from a large nationally representative Australian population survey
This article has 6 authors:Reviewed by ScreenIT
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The spike protein of SARS-CoV-2 induces endothelial inflammation through integrin α5β1 and NF-κB signaling
This article has 6 authors:Reviewed by ScreenIT
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Cash versus Lotteries: COVID-19 Vaccine Incentives Experiment*
This article has 6 authors:Reviewed by ScreenIT
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A Multi-Site Analysis of the Prevalence of Food Insecurity in the United States, before and during the COVID-19 Pandemic
This article has 69 authors:Reviewed by ScreenIT
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Executable network of SARS-CoV-2-host interaction predicts drug combination treatments
This article has 11 authors:Reviewed by ScreenIT
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Differential Interactions between Human ACE2 and Spike RBD of SARS-CoV-2 Variants of Concern
This article has 7 authors:Reviewed by ScreenIT