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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High Neutralizing Antibody Levels Against Severe Acute Respiratory Syndrome Coronavirus 2 Omicron BA.1 and BA.2 After UB-612 Vaccine Booster
This article has 13 authors:Reviewed by ScreenIT
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Medical students’ crisis-induced stress and the association with social support
This article has 5 authors:Reviewed by ScreenIT
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Modifications to student quarantine policies in K–12 schools implementing multiple COVID-19 prevention strategies restores in-person education without increasing SARS-CoV-2 transmission risk, January-March 2021
This article has 31 authors:Reviewed by ScreenIT
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Fifteen-Month Follow-Up of Anti-Spike Receptor-Binding Domain SARS-CoV-2 Antibodies among Healthcare Workers in Boston, MA
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron spike H655Y mutation is responsible for enhancement of the endosomal entry pathway and reduction of cell surface entry pathways
This article has 6 authors:Reviewed by ScreenIT
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Persistent immune and clotting dysfunction detected in saliva and blood plasma after COVID-19
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike proteins uptake mediated by lipid raft ganglioside GM1 in human cerebrovascular cells
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 testing protocols to guide duration of isolation: a cost-effectiveness analysis
This article has 2 authors:Reviewed by ScreenIT
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A fast and sensitive absolute quantification assay for the detection of SARS-CoV-2 peptides using parallel reaction monitoring mass spectrometry
This article has 7 authors:Reviewed by ScreenIT
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Critically ill COVID-19 patients with neutralizing autoantibodies against type I interferons have increased risk of herpesvirus disease
This article has 9 authors:Reviewed by ScreenIT