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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Potent neutralization of SARS-CoV-2 variants of concern by an antibody with an uncommon genetic signature and structural mode of spike recognition
This article has 23 authors:Reviewed by ScreenIT
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Effectiveness of BNT162b2 mRNA vaccine and ChAdOx1 adenovirus vector vaccine on mortality following COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Vaccination against COVID-19 and society’s return to normality in England: a modelling study of impacts of different types of naturally acquired and vaccine-induced immunity
This article has 2 authors:Reviewed by ScreenIT
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Indian Interventional trials for COVID-19 drugs: Insights and Learnings
This article has 5 authors:Reviewed by ScreenIT
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Detection of Antibody Responses Against SARS-CoV-2 in Plasma and Saliva From Vaccinated and Infected Individuals
This article has 18 authors:Reviewed by ScreenIT
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Individuals who were mildly symptomatic following infection with SARS-CoV-2 B.1.1.28 have neutralizing antibodies to the P.1 variant
This article has 10 authors:Reviewed by ScreenIT
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An intranasal ASO therapeutic targeting SARS-CoV-2
This article has 23 authors:Reviewed by ScreenIT
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Microsimulation of SARS-CoV-2 Transmission in Society
This article has 3 authors:Reviewed by ScreenIT
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Evaluation of high flow local extraction for controlling aerosol plumes in operating theaters
This article has 4 authors:Reviewed by ScreenIT
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Allicin inhibits SARS-CoV-2 replication and abrogates the antiviral host response in the Calu-3 proteome
This article has 8 authors:Reviewed by ScreenIT