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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Ebselen derivatives are very potent dual inhibitors of SARS-CoV-2 proteases - PL pro and M pro in in vitro studies
This article has 14 authors:Reviewed by ScreenIT
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High prevalence of SARS-CoV-2 swab positivity in England during September 2020: interim report of round 5 of REACT-1 study
This article has 15 authors:Reviewed by ScreenIT
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Childhood asthma outcomes during the COVID‐19 pandemic: Findings from the PeARL multi‐national cohort
This article has 43 authors:Reviewed by ScreenIT
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Designed variants of ACE2-Fc that decouple anti-SARS-CoV-2 activities from unwanted cardiovascular effects
This article has 4 authors:Reviewed by ScreenIT
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Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia
This article has 6 authors:Reviewed by ScreenIT
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Association among income loss, financial strain and depressive symptoms during COVID-19: Evidence from two longitudinal studies
This article has 17 authors:Reviewed by ScreenIT
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Dataset of COVID-19 outbreak and potential predictive features in the USA
This article has 8 authors:Reviewed by ScreenIT
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Excess deaths associated with the Iranian COVID-19 epidemic: A province-level analysis
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 Outcomes Among Persons Living With or Without Diagnosed HIV Infection in New York State
This article has 13 authors:Reviewed by ScreenIT
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Liquid Chalk Is an Antiseptic against SARS-CoV-2 and Influenza A Respiratory Viruses
This article has 6 authors:Reviewed by ScreenIT