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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SARS-CoV and SARS-CoV-2 are transmitted through the air between ferrets over more than one meter distance
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 Variant of Concern 202012/01 Has about Twofold Replicative Advantage and Acquires Concerning Mutations
This article has 5 authors:Reviewed by ScreenIT
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Maternal and perinatal characteristics and outcomes of pregnancies complicated with COVID-19 in Kuwait
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV-2 antibody-positivity protects against reinfection for at least seven months with 95% efficacy
This article has 23 authors:Reviewed by ScreenIT
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Estimating dates of origin and end of COVID-19 epidemics
This article has 4 authors:Reviewed by ScreenIT
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The ground-level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland
This article has 3 authors:Reviewed by ScreenIT
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Identification of bis-benzylisoquinoline alkaloids as SARS-CoV-2 entry inhibitors from a library of natural products in vitro
This article has 10 authors:Reviewed by ScreenIT
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Hundreds of severe pediatric COVID-19 infections in Wuhan prior to the lockdown
This article has 4 authors:Reviewed by ScreenIT
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Prevalence and Clinical Correlates of COVID-19 Outbreak Among Health Care Workers in a Tertiary Level Hospital in Delhi
This article has 6 authors:Reviewed by ScreenIT
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Transmission of COVID-19 in 282 clusters in Catalonia, Spain: a cohort study
This article has 18 authors:Reviewed by ScreenIT