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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ChAdOx1 nCoV-19 Vaccine Side Effects among Healthcare Workers in Trinidad and Tobago
This article has 3 authors:Reviewed by ScreenIT
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A study of the benefits of vaccine mandates and vaccine passports for SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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Casirivimab and Imdevimab for the Treatment of Hospitalized Patients With COVID-19
This article has 34 authors:Reviewed by ScreenIT
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PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease
This article has 10 authors:Reviewed by ScreenIT
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The β-NGF/TrkA Signalling Pathway Is Associated With the Production of Anti-Nucleoprotein IgG in Convalescent COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Severe Acute Respiratory Syndrome Coronavirus 2 Delta Vaccine Breakthrough Transmissibility in Alachua County, Florida
This article has 22 authors:Reviewed by ScreenIT
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Could widespread use of antiviral treatment curb the COVID-19 pandemic? A modeling study
This article has 5 authors:Reviewed by ScreenIT
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Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data
This article has 48 authors:Reviewed by ScreenIT
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Vaccine effectiveness against COVID-19 related hospital admission in the Netherlands: A test-negative case-control study
This article has 5 authors:Reviewed by ScreenIT
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Analysis of Immune Escape Variants from Antibody-Based Therapeutics against COVID-19: A Systematic Review
This article has 5 authors:Reviewed by ScreenIT