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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Genomic diversity of SARS-CoV-2 can be accelerated by mutations in the nsp14 gene
This article has 8 authors:Reviewed by ScreenIT
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High COVID-19 incidence among Norwegian travellers returned from Lombardy: implications for travel restrictions
This article has 2 authors:Reviewed by ScreenIT
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The relationship between neighborhood poverty and COVID-19 mortality within racial/ethnic groups (Cook County, Illinois)
This article has 2 authors:Reviewed by ScreenIT, Rapid Reviews Infectious Diseases
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Analysis of epidemiological characteristics of coronavirus 2019 infection and preventive measures in Shenzhen China—a heavy population city
This article has 7 authors:Reviewed by ScreenIT
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Multimerization- and glycosylation-dependent receptor binding of SARS-CoV-2 spike proteins
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 Testing in Florida, Illinois, and Maryland: Access and Barriers
This article has 10 authors:Reviewed by ScreenIT
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Regulation of the ACE2 locus in human airways cells
This article has 3 authors:Reviewed by ScreenIT
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A Two-Region SEIR COVID-19 Epidemic Model for the Island of Ireland
This article has 2 authors:Reviewed by ScreenIT
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Rapid Scoping Review of Evidence of Outdoor Transmission of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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CATALYST trial protocol: a multicentre, open-label, phase II, multiarm trial for an early and accelerated evaluation of the potential treatments for COVID-19 in hospitalised adults
This article has 16 authors:Reviewed by ScreenIT