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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Impact of COVID-19 on the oncological outcomes of colorectal cancer surgery in northern Italy in 2019 and 2020: multicentre comparative cohort study
This article has 138 authors:Reviewed by ScreenIT
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The localized rise of a B.1.526 SARS-CoV-2 variant containing an E484K mutation in New York State
This article has 5 authors:Reviewed by ScreenIT
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Phylogenetic estimates of SARS-CoV-2 introductions into Washington State
This article has 10 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on gastrointestinal infection trends in England, February–July 2020
This article has 11 authors:Reviewed by ScreenIT
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EUAdb: A resource for COVID-19 test development and comparison
This article has 8 authors:Reviewed by ScreenIT
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The impact of COVID-19 pandemic on AMI and stroke mortality in Lombardy: Evidence from the epicenter of the pandemic
This article has 9 authors:Reviewed by ScreenIT
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Pre-pandemic cognitive function and COVID-19 vaccine hesitancy: cohort study
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike L452R variant evades cellular immunity and increases infectivity
This article has 27 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Bioinformatics analysis of SARS-CoV-2 RBD mutant variants and insights into antibody and ACE2 receptor binding
This article has 4 authors:Reviewed by ScreenIT
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Estimating the strength of selection for new SARS-CoV-2 variants
This article has 5 authors:Reviewed by ScreenIT