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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Multivariate Analyses of Codon Usage of SARS-CoV-2 and other betacoronaviruses
This article has 4 authors:Reviewed by ScreenIT
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Mucin 4 Protects Female Mice from Coronavirus Pathogenesis
This article has 11 authors:Reviewed by ScreenIT
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Clinical features and progression of acute respiratory distress syndrome in coronavirus disease 2019
This article has 7 authors:Reviewed by ScreenIT
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Anxiety levels, precautionary behaviours and public perceptions during the early phase of the COVID-19 outbreak in China: a population-based cross-sectional survey
This article has 7 authors:Reviewed by ScreenIT
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Kidney disease is associated with in-hospital death of patients with COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19)
This article has 15 authors:Reviewed by ScreenIT
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Association between population migration and epidemic control of Coronavirus disease 2019
This article has 7 authors:Reviewed by ScreenIT
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Estimating the cure rate and case fatality rate of the ongoing epidemic COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model
This article has 7 authors:Reviewed by ScreenIT
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The reproductive number R 0 of COVID-19 based on estimate of a statistical time delay dynamical system
This article has 3 authors:Reviewed by ScreenIT