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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Endotoxemia and circulating bacteriome in severe COVID-19 patients
This article has 32 authors:Reviewed by ScreenIT
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Pooling for SARS-CoV-2 control in care institutions
This article has 9 authors:Reviewed by ScreenIT
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The Mathematics of Testing with Application to Prevalence of COVID-19
This article has 1 author:Reviewed by ScreenIT
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Greater risk of severe COVID-19 in Black, Asian and Minority Ethnic populations is not explained by cardiometabolic, socioeconomic or behavioural factors, or by 25(OH)-vitamin D status: study of 1326 cases from the UK Biobank
This article has 9 authors:Reviewed by ScreenIT
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Trauma-spectrum symptoms among the Italian general population in the time of the COVID-19 outbreak
This article has 10 authors:Reviewed by ScreenIT
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Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications
This article has 3 authors:Reviewed by ScreenIT
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COVID-19: Why SOLIDARITY and DisCoVeRy trials may fail to bring informative and timely results
This article has 6 authors:Reviewed by ScreenIT
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Mathematical Modeling and Analysis of COVID-19 pandemic in Nigeria
This article has 4 authors:Reviewed by ScreenIT
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Antibody Profiling of COVID-19 Patients in an Urban Low-Incidence Region in Northern Germany
This article has 9 authors:Reviewed by ScreenIT
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CIGB-258 immunomodulatory peptide: a novel promising treatment for critical and severe COVID-19 patients
This article has 16 authors:Reviewed by ScreenIT