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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Diagnostic value of symptoms for pediatric SARS-CoV-2 infection in a primary care setting
This article has 7 authors:Reviewed by ScreenIT
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Clinical correlation of lung ultrasound profiles in patients with COVID-19 infection
This article has 9 authors:Reviewed by ScreenIT
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Upper respiratory tract SARS-CoV-2 RNA loads in symptomatic and asymptomatic children and adults
This article has 13 authors:Reviewed by ScreenIT
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SARS-CoV-2 Seroprevalence in 12 Cities of India from July-December 2020
This article has 9 authors:Reviewed by ScreenIT
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A comprehensive analysis of outcomes between COVID-19 patients with an elevated serum lipase compared to those with pancreatitis
This article has 8 authors:Reviewed by ScreenIT
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INTRANASAL APPLICATION OF LACTOCOCCUS LACTIS W 136 BACTERIA EARLY IN SARS-Cov-2 INFECTION MAY HAVE A BENEFICIAL IMMUNOMODULATORY EFFECT: A PROOF-OF-CONCEPT STUDY
This article has 4 authors:Reviewed by ScreenIT
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Quantatitive Analysis of Conserved Sites on the SARS-CoV-2 Receptor-Binding Domain to Promote Development of Universal SARS-Like Coronavirus Vaccines
This article has 20 authors:Reviewed by ScreenIT
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Natural selection in the evolution of SARS-CoV-2 in bats, not humans, created a highly capable human pathogen
This article has 8 authors:Reviewed by ScreenIT
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Computational insights into differential interaction of mamalian ACE2 with the SARS-CoV-2 spike receptor binding domain
This article has 5 authors:Reviewed by ScreenIT
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Recognition of Divergent Viral Substrates by the SARS-CoV-2 Main Protease
This article has 6 authors:Reviewed by ScreenIT