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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A Systems Approach to Assess Transport and Diffusion of Hazardous Airborne Particles in a Large Surgical Suite: Potential Impacts on Viral Airborne Transmission
This article has 3 authors:Reviewed by ScreenIT
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Resuming professional football (soccer) during the COVID-19 pandemic in a country with high infection rates: a prospective cohort study
This article has 11 authors:Reviewed by ScreenIT
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Heparan sulfate assists SARS-CoV-2 in cell entry and can be targeted by approved drugs in vitro
This article has 17 authors:Reviewed by ScreenIT
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Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine, BBV152: interim results from a double-blind, randomised, multicentre, phase 2 trial, and 3-month follow-up of a double-blind, randomised phase 1 trial
This article has 26 authors: -
Impact of healthcare worker shift scheduling on workforce preservation during the COVID-19 pandemic
This article has 10 authors:Reviewed by ScreenIT
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Quantifying SARS-CoV-2 spread in Switzerland based on genomic sequencing data
This article has 41 authors:Reviewed by ScreenIT
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Baseline cardiometabolic profiles and SARS-CoV-2 infection in the UK Biobank
This article has 6 authors:Reviewed by ScreenIT
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Emergence of an early SARS-CoV-2 epidemic in the United States
This article has 52 authors:Reviewed by ScreenIT
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Mobility network models of COVID-19 explain inequities and inform reopening
This article has 7 authors:Reviewed by ScreenIT
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Between-centre differences for COVID-19 ICU mortality from early data in England
This article has 4 authors:Reviewed by ScreenIT