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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Longitudinal analyses reveal immunological misfiring in severe COVID-19
This article has 101 authors:Reviewed by ScreenIT
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A Multiplex Microsphere IgG Assay for SARS-CoV-2 Using ACE2-Mediated Inhibition as a Surrogate for Neutralization
This article has 14 authors:Reviewed by ScreenIT
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Competing health risks associated with the COVID-19 pandemic and early response: A scoping review
This article has 13 authors:Reviewed by ScreenIT
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Melatonin is significantly associated with survival of intubated COVID-19 patients
This article has 3 authors:Reviewed by ScreenIT
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Prevalence of SARS-CoV-2 IgG antibodies in a population from Veracruz (Southeastern Mexico)
This article has 7 authors:Reviewed by ScreenIT
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Sociodemographic characteristics and COVID-19 testing rates: spatiotemporal patterns and impact of test accessibility in Sweden
This article has 13 authors:Reviewed by ScreenIT
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Work-related and personal predictors of COVID-19 transmission: evidence from the UK and USA
This article has 8 authors:Reviewed by ScreenIT
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Search for the trend of COVID-19 infection following Farr’s law, IDEA model and power law
This article has 3 authors:Reviewed by ScreenIT
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Recombinant ACE2 Expression Is Required for SARS-CoV-2 To Infect Primary Human Endothelial Cells and Induce Inflammatory and Procoagulative Responses
This article has 4 authors:Reviewed by ScreenIT
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The Repurposed Drugs Suramin and Quinacrine Cooperatively Inhibit SARS-CoV-2 3CLpro In Vitro
This article has 7 authors:Reviewed by ScreenIT