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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Serological testing in addition to PCR screening for the re-opening of American colleges and universities: potential for cost-savings without compromising pandemic mitigation
This article has 5 authors:Reviewed by ScreenIT
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Poor Metabolic Health Increases COVID-19-Related Mortality in the UK Biobank Sample
This article has 2 authors:Reviewed by ScreenIT
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Red Blood Cell Distribution Width in Hospitalized COVID-19 Patients
This article has 7 authors:Reviewed by ScreenIT
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Predicting the Emergence of SARS-CoV-2 Clades
This article has 4 authors:Reviewed by ScreenIT
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Prevalence and outcomes of co-infection and superinfection with SARS-CoV-2 and other pathogens: A systematic review and meta-analysis
This article has 6 authors:Reviewed by ScreenIT
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Identification of key genes in SARS-CoV-2 patients on bioinformatics analysis
This article has 2 authors:Reviewed by ScreenIT
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Long-term predictions for COVID-19 pandemic dynamics in Ukraine, Austria and Italy
This article has 1 author:Reviewed by ScreenIT
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The sensitivity of SARS-CoV-2 antigen tests in the view of large-scale testing
This article has 7 authors:Reviewed by ScreenIT
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Management of Acute Appendicitis in Children During COVID-19 and Perspectives of Pediatric Surgeons From South Asia: Survey Study
This article has 6 authors:Reviewed by ScreenIT
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Multifractal Analysis of SARS-CoV-2 Coronavirus genomes using the wavelet transform
This article has 1 author:Reviewed by ScreenIT