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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Aglycone polyether ionophores as broad-spectrum agents inhibit multiple enveloped viruses including SARS-CoV-2 in vitro and successfully cure JEV infected mice
This article has 12 authors:Reviewed by ScreenIT
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Double Lock of a Potent Human Monoclonal Antibody against SARS-CoV-2
This article has 32 authors:Reviewed by ScreenIT
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Modeling of COVID-19 Outbreak Indicators in China Between January and June
This article has 3 authors:Reviewed by ScreenIT
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REACT-1 round 7 updated report: regional heterogeneity in changes in prevalence of SARS-CoV-2 infection during the second national COVID-19 lockdown in England
This article has 15 authors:Reviewed by ScreenIT
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A Test-Based Strategy for Safely Shortening Quarantine for COVID-19
This article has 3 authors:Reviewed by ScreenIT
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A Healthy Buildings Guideline for the COVID-19 Pandemic and Beyond
This article has 1 author:Reviewed by ScreenIT
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Parents’ and guardians’ views on the acceptability of a future COVID-19 vaccine: A multi-methods study in England
This article has 5 authors:Reviewed by ScreenIT
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Diagnostic and monitoring utilities of saliva for SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Point-of-care CRISPR-Cas-assisted SARS-CoV-2 detection in an automated and portable droplet magnetofluidic device
This article has 10 authors:Reviewed by ScreenIT
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Cost and social distancing dynamics in a mathematical model of COVID-19 with application to Ontario, Canada
This article has 3 authors:Reviewed by ScreenIT