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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Recruitment of highly cytotoxic CD8+ T cell receptors in mild SARS-CoV-2 infection
This article has 32 authors:Reviewed by ScreenIT
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Effective presence of antibodies against common human coronaviruses in immunoglobulin medicinal products
This article has 3 authors:Reviewed by ScreenIT
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Robust and durable serological response following pediatric SARS-CoV-2 infection
This article has 50 authors:Reviewed by ScreenIT
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RNA Viromics of Southern California Wastewater and Detection of SARS-CoV-2 Single-Nucleotide Variants
This article has 13 authors:Reviewed by ScreenIT
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CoVizu: Rapid analysis and visualization of the global diversity of SARS-CoV-2 genomes
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 incidence, transmission, and reinfection in a rural and an urban setting: results of the PHIRST-C cohort study, South Africa, 2020–21
This article has 44 authors:Reviewed by ScreenIT
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Plasma cell-free RNA characteristics in COVID-19 patients
This article has 41 authors:Reviewed by ScreenIT
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SARS-CoV-2 Genomic Surveillance Reveals Little Spread Between a Large University Campus and the Surrounding Community
This article has 12 authors:Reviewed by ScreenIT
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Recovery of SARS-CoV-2 from large volumes of raw wastewater is enhanced with the inuvai R180 system
This article has 13 authors:Reviewed by ScreenIT
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Using household rosters from survey data to estimate all-cause excess death rates during the COVID pandemic in India
This article has 2 authors:Reviewed by ScreenIT