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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Progressing adaptation of SARS-CoV-2 to humans
This article has 1 author:Reviewed by ScreenIT
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COVID-19: One-month impact of the French lockdown on the epidemic burden
This article has 3 authors:Reviewed by ScreenIT
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In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT
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The Algerian Chapter of SARS-CoV-2 Pandemic: An Evolutionary, Genetic, and Epidemiological Prospect
This article has 7 authors:Reviewed by ScreenIT
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The safety and immunogenicity of an inactivated SARS-CoV-2 vaccine in Chinese adults aged 18–59 years: A phase I randomized, double-blinded, controlled trial
This article has 47 authors: -
ABO-RH blood group and risk of covid-19 in a moroccan population
This article has 7 authors:Reviewed by ScreenIT
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Hydroxychloroquine plus azithromycin: a potential interest in reducing in-hospital morbidity due to COVID-19 pneumonia (HI-ZY-COVID)?
This article has 13 authors:Reviewed by ScreenIT
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Intrafamilial Exposure to SARS-CoV-2 Associated with Cellular Immune Response without Seroconversion, France
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 Trend and Forecast in India: A Joinpoint Regression Analysis
This article has 1 author:Reviewed by ScreenIT
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The impact of Spike mutations on SARS-CoV-2 neutralization
This article has 21 authors:Reviewed by ScreenIT