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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Effect of Subcutaneous Casirivimab and Imdevimab Antibody Combination vs Placebo on Development of Symptomatic COVID-19 in Early Asymptomatic SARS-CoV-2 Infection
This article has 768 authors:Reviewed by ScreenIT
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Impact of COVID-19 pandemic on sickness absence for mental ill health in National Health Service staff
This article has 8 authors:Reviewed by ScreenIT
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Role of hemogram-derived ratios and systemic-Immune inflammation index in prediction of COVID-19 progression in Egyptian patients
This article has 7 authors:Reviewed by ScreenIT
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Association of Disease-Modifying Therapies with COVID-19 Susceptibility and Severity in Patients with Multiple Sclerosis: A Systematic Review and Network Meta-Analysis
This article has 10 authors:Reviewed by ScreenIT
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Moral injury and well-being in essential workers during the COVID-19 pandemic: local survey findings
This article has 4 authors:Reviewed by ScreenIT
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Importance of adequate COVID-19 case definitions in the SARS-CoV-2 pandemic
This article has 3 authors:Reviewed by ScreenIT
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Survey of COVID-19 associated symptoms and reported deaths in an urban community in Kano, Nigeria
This article has 5 authors:Reviewed by ScreenIT
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Zinc 2+ ion inhibits SARS-CoV-2 main protease and viral replication in vitro
This article has 14 authors:Reviewed by ScreenIT
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Grouping theory of epidemiology
This article has 2 authors:Reviewed by ScreenIT
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Prevalence and circulation patterns of SARS-CoV-2 variants in European sewage mirror clinical data of 54 European cities
This article has 10 authors:Reviewed by ScreenIT