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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High affinity modified ACE2 receptors protect from SARS-CoV-2 infection in hamsters
This article has 18 authors:Reviewed by ScreenIT
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Accuracy of automated computer aided-risk scoring systems to estimate the risk of COVID-19 and in-hospital mortality: a retrospective cohort study
This article has 5 authors:Reviewed by ScreenIT
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Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19
This article has 11 authors:Reviewed by ScreenIT
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Rapid in vitro assays for screening neutralizing antibodies and antivirals against SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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The time-series ages distribution of the reported COVID-2019 infected people suggests the undetected local spreading of COVID-2019 in Hubei and Guangdong provinces before 19 th Jan 2020
This article has 2 authors:Reviewed by ScreenIT
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Outcome of COVID-19 and Match-Population Analysis with Compassionate Use of Remdesivir
This article has 3 authors:Reviewed by ScreenIT
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Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study
This article has 5 authors:Reviewed by ScreenIT
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The work characteristics and social distancing at the manufacturing workplace
This article has 1 author:Reviewed by ScreenIT
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On the molecular mechanism of SARS-CoV-2 retention in the upper respiratory tract
This article has 3 authors:Reviewed by ScreenIT
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Application of a 27-protein candidate cardiovascular surrogate endpoint to track risk ascendancy and resolution in COVID-19
This article has 18 authors:Reviewed by ScreenIT