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 lockdown COVID-19 seroprevalence and circulation at the time of delivery, France
This article has 10 authors:Reviewed by ScreenIT
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Differential methylation as a mediator of COVID-19 susceptibility
This article has 4 authors:Reviewed by ScreenIT
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A high-affinity RBD-targeting nanobody improves fusion partner’s potency against SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning
This article has 10 authors:Reviewed by ScreenIT
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The protective effect of SARS-CoV-2 antibodies in Scottish healthcare workers
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Amilorides inhibit SARS-CoV-2 replication in vitro by targeting RNA structures
This article has 16 authors:Reviewed by ScreenIT
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Tracking SARS-CoV-2 RNA through the Wastewater Treatment Process
This article has 9 authors:Reviewed by ScreenIT
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Making sense of the Global Coronavirus Data: The role of testing rates in understanding the pandemic and our exit strategy
This article has 2 authors:Reviewed by ScreenIT
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Nationwide SARS-CoV-2 Surveillance Study for Sewage and Sludges of Wastewater Treatment Plants in Turkey
This article has 8 authors:Reviewed by ScreenIT
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Efficacy and safety of tocilizumab in the management of COVID-19: a systematic review and meta-analysis of observational studies
This article has 3 authors:Reviewed by ScreenIT