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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Puerto Rico Health System Resilience After Hurricane Maria: Implications for Disaster Preparedness in the COVID-19 Era
This article has 8 authors:Reviewed by ScreenIT
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A Sew-Free Origami Mask for Improvised Respiratory Protection
This article has 5 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Sub-weekly cycle uncovers the hidden link of atmospheric pollution to Kawasaki Disease
This article has 5 authors:Reviewed by ScreenIT
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Clinical, cerebrospinal fluid, and neuroimaging findings in COVID-19 encephalopathy: a case series
This article has 27 authors:Reviewed by ScreenIT
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COVID-19 antibody seroprevalence in Santa Clara County, California
This article has 15 authors:Reviewed by ScreenIT
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Potential biochemical markers to identify severe cases among COVID-19 patients
This article has 7 authors:Reviewed by ScreenIT
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Identification of 14 Known Drugs as Inhibitors of the Main Protease of SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Optimizing Vaccine Allocation to Combat the COVID-19 Pandemic
This article has 7 authors:Reviewed by ScreenIT
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Precautionary breaks: Planned, limited duration circuit breaks to control the prevalence of SARS-CoV2 and the burden of COVID-19 disease
This article has 6 authors:Reviewed by ScreenIT
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Mobility and COVID-19 in Andorra: Country-Scale Analysis of High-Resolution Mobility Patterns and Infection Spread
This article has 8 authors:Reviewed by ScreenIT