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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Trends in suicide rates during the COVID-19 pandemic restrictions in a major German city
This article has 6 authors:Reviewed by ScreenIT
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Inferring Toll-Like Receptor induced epitope subunit vaccine candidate against SARS-CoV-2: A Reverse Vaccinology approach
This article has 7 authors:Reviewed by ScreenIT
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A sensitive and affordable multiplex RT-qPCR assay for SARS-CoV-2 detection
This article has 38 authors:Reviewed by Review Commons, ScreenIT
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COVID-19: How Many Years of Life Lost?
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 in a rural health system in New York - case series and an approach to management
This article has 10 authors:Reviewed by ScreenIT
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International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study
This article has 86 authors:Reviewed by ScreenIT
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Association between the dynamics of the COVID-19 epidemic and ABO blood type distribution
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 Growth in Rural versus Urban Counties with Major Universities at the Start of the 2020 Academic Year
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Triggers an MDA-5-Dependent Interferon Response Which Is Unable To Control Replication in Lung Epithelial Cells
This article has 11 authors:Reviewed by ScreenIT
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Structural dynamics of single SARS-CoV-2 pseudoknot molecules reveal topologically distinct conformers
This article has 9 authors:Reviewed by ScreenIT