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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Xeno-Nucleic Acid (XNA) 2’-Fluoro-Arabino Nucleic Acid (FANA) Aptamers to the Receptor-Binding Domain of SARS-CoV-2 S Protein Block ACE2 Binding
This article has 2 authors:Reviewed by ScreenIT
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A Rapid Saliva Test for Monitoring Immune Protection against SARS -CoV-2 and its Variants
This article has 7 authors:Reviewed by ScreenIT
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Detection and whole-genome sequencing of SARS-CoV-2 B.1.617.2 and B.1.351 variants of concern from Pakistan during the COVID-19 third wave
This article has 9 authors:Reviewed by ScreenIT
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A modular protein subunit vaccine candidate produced in yeast confers protection against SARS-CoV-2 in non-human primates
This article has 34 authors:Reviewed by ScreenIT
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Modeling COVID-19 vaccine efficacy and coverage towards herd-immunity in the Basque Country, Spain
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 seroprevalence in asymptomatic or mild symptomatic people and symptomatic patients with negative PCR results: The hidden perspective in epidemiological reports
This article has 12 authors:Reviewed by ScreenIT
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Time-to-event assessment for the discovery of the proper prognostic value of clinical biomarkers optimized for COVID-19
This article has 1 author:Reviewed by ScreenIT
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Case-control study of neuropsychiatric symptoms in electronic health records following COVID-19 hospitalization in 2 academic health systems
This article has 5 authors:Reviewed by ScreenIT
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Quantifying social contact patterns in Minnesota during Stay-at-Home social distancing order
This article has 6 authors:Reviewed by ScreenIT
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Adding a reaction-restoration type transmission rate dynamic-law to the basic SEIR COVID-19 model
This article has 2 authors:Reviewed by ScreenIT