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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Chitinase 3-like-1 is a Therapeutic Target That Mediates the Effects of Aging in COVID-19
This article has 15 authors:Reviewed by ScreenIT
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An improved and readily available version of Bst DNA Polymerase for LAMP, and applications to COVID-19 diagnostics
This article has 5 authors:Reviewed by ScreenIT
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The COVID-19 Spread Patterns in Italy and India: A Comparison of the Current Situation
This article has 1 author:Reviewed by ScreenIT
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Medical vulnerability of individuals with Down syndrome to severe COVID-19–data from the Trisomy 21 Research Society and the UK ISARIC4C survey
This article has 22 authors:Reviewed by ScreenIT
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Effects of universal masking on Massachusetts healthcare workers’ COVID-19 incidence
This article has 7 authors:Reviewed by ScreenIT
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Phased Implementation of COVID-19 Vaccination: Rapid Assessment of Policy Adoption, Reach and Effectiveness to Protect the Most Vulnerable in the US
This article has 5 authors:Reviewed by ScreenIT
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National Consumption of Antimalarial Drugs and COVID-19 Deaths Dynamics: An Ecological Study
This article has 1 author:Reviewed by ScreenIT
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Artificial intelligence to predict the risk of mortality from Covid-19: Insights from a Canadian Application
This article has 6 authors:Reviewed by ScreenIT
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The importance of supplementary immunisation activities to prevent measles outbreaks during the COVID-19 pandemic in Kenya
This article has 19 authors:Reviewed by ScreenIT
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Estimation of undetected COVID-19 infections in India
This article has 2 authors:Reviewed by ScreenIT