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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Post-Infection Entry Mechanism of Ricin A Chain-Pokeweed Antiviral Proteins (RTA-PAPs) Chimeras is Mediated by Viroporins
This article has 1 author:Reviewed by ScreenIT
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Enhanced fusogenicity and pathogenicity of SARS-CoV-2 Delta P681R mutation
This article has 57 authors:Reviewed by ScreenIT
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A randomised controlled trial of effectiveness and safety of Niclosamide as add on therapy to the standard of care measures in COVID-19 management
This article has 7 authors:Reviewed by ScreenIT
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Coadministration of AYUSH 64 as an adjunct to Standard of Care in mild and moderate COVID-19: A randomised, controlled, multicentric clinical trial
This article has 17 authors:Reviewed by ScreenIT
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Similar Rates of AKI during the First Two Waves of COVID-19 in Northern Italy: a single-center study
This article has 20 authors:Reviewed by ScreenIT
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Casirivimab and imdevimab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial
This article has 35 authors:Reviewed by ScreenIT
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Serological prevalence of SARS-CoV-2 antibody among children and young age group (between 2 and 17 years) in India: An interim result from a large multicentric population-based seroepidemiological study
This article has 19 authors:Reviewed by ScreenIT
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A stem-loop RNA RIG-I agonist protects against acute and chronic SARS-CoV-2 infection in mice
This article has 26 authors:Reviewed by ScreenIT
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Social contact patterns and implications for infectious disease transmission – a systematic review and meta-analysis of contact surveys
This article has 34 authors:Reviewed by ScreenIT
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Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm
This article has 2 authors:Reviewed by ScreenIT