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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Androgen Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men
This article has 13 authors:Reviewed by ScreenIT
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Performance of Abbott ID NOW COVID-19 rapid nucleic acid amplification test in nasopharyngeal swabs transported in viral media and dry nasal swabs, in a New York City academic institution
This article has 8 authors:Reviewed by ScreenIT
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Characterization of neutralizing antibodies from a SARS-CoV-2 infected individual
This article has 19 authors:Reviewed by ScreenIT
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Clinical, radiological and therapeutic characteristics of patients with COVID-19 in Saudi Arabia
This article has 14 authors:Reviewed by ScreenIT
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Local computational methods to improve the interpretability and analysis of cryo-EM maps
This article has 9 authors:Reviewed by ScreenIT
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The SARS-CoV-2 conserved macrodomain is a mono-ADP-ribosylhydrolase
This article has 13 authors:Reviewed by ScreenIT
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A putative new SARS-CoV protein, 3a*, encoded in an ORF overlapping ORF3a
This article has 1 author:Reviewed by ScreenIT
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Comparative analysis of antiviral efficacy of FDA-approved drugs against SARS-CoV-2 in human lung cells: Nafamostat is the most potent antiviral drug candidate
This article has 4 authors:Reviewed by ScreenIT
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COVID-19: Predictive Mathematical Models for the Number of Deaths in South Korea, Italy, Spain, France, UK, Germany, and USA
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 transmission risk factors
This article has 2 authors:Reviewed by ScreenIT