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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Epidemiological Study of COVID-19 Infections: Case of Ga East Municipal Hospital Treatment Centre - Kwabenya-Ghana
This article has 3 authors:Reviewed by ScreenIT
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Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy
This article has 70 authors:Reviewed by ScreenIT
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COVID-19 Testing and Case Rates and Social Contact Among Residential College Students in Connecticut During the 2020-2021 Academic Year
This article has 6 authors:Reviewed by ScreenIT
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Molecular and Serologic Investigation of the 2021 COVID-19 Case Surge Among Vaccine Recipients in Mongolia
This article has 7 authors:Reviewed by ScreenIT
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Changing Dynamics of COVID-19 in the U.S. with the Emergence of the Delta Variant: Projections of the COVID-19 Simulator
This article has 8 authors:Reviewed by ScreenIT
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Breastfeeding Practices Among Mothers During COVID-19 in India
This article has 3 authors:Reviewed by ScreenIT
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Comparison of two highly-effective mRNA vaccines for COVID-19 during periods of Alpha and Delta variant prevalence
This article has 12 authors:Reviewed by ScreenIT
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Reprogramming of the intestinal epithelial-immune cell interactome during SARS-CoV-2 infection
This article has 17 authors:Reviewed by ScreenIT
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An efficient immunoassay for the B cell help function of SARS-CoV-2-specific memory CD4+ T cells
This article has 8 authors:Reviewed by ScreenIT
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Fully Human Antibody Immunoglobulin from Transchromosomic Bovines is Potent Against SARS-CoV-2 Variant Pseudoviruses
This article has 5 authors:Reviewed by ScreenIT