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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Altered increase in STAT1 expression and phosphorylation in severe COVID‐19
This article has 13 authors:Reviewed by ScreenIT
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A Multidimensional Cross-Sectional Analysis of Coronavirus Disease 2019 Seroprevalence Among a Police Officer Cohort: The PoliCOV-19 Study
This article has 16 authors:Reviewed by ScreenIT
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Speeding and Traffic-Related Injuries and Fatalities during the 2020 COVID-19 Pandemic: The Cases of Seattle and New York City
This article has 2 authors:Reviewed by ScreenIT
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Specificity of SARS-CoV-2 Antibody Detection Assays against S and N Proteins among Pre-COVID-19 Sera from Patients with Protozoan and Helminth Parasitic Infections
This article has 13 authors:Reviewed by ScreenIT
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Delta spike P681R mutation enhances SARS-CoV-2 fitness over Alpha variant
This article has 12 authors:Reviewed by ScreenIT
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High genetic barrier to SARS-CoV-2 polyclonal neutralizing antibody escape
This article has 14 authors:Reviewed by ScreenIT
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Clinical course impacts early kinetics,magnitude, and amplitude of SARS-CoV-2 neutralizing antibodies beyond 1 year after infection
This article has 22 authors:Reviewed by ScreenIT
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In-House, Rapid, and Low-Cost SARS-CoV-2 Spike Gene Sequencing Protocol to Identify Variants of Concern Using Sanger Sequencing
This article has 14 authors:Reviewed by ScreenIT
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The COVID-19 Pandemic and Early Child Cognitive Development: A Comparison of Development in Children Born During the Pandemic and Historical References
This article has 5 authors:Reviewed by ScreenIT
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Coronavirus Disease 2019 Outcomes Among Recipients of Anti‐CD20 Monoclonal Antibodies for Immune‐Mediated Diseases: A Comparative Cohort Study
This article has 13 authors:Reviewed by ScreenIT