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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Sentimental Tweets Classification of Symptomatic COVID-19
This article has 1 author:Reviewed by ScreenIT
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The Place of Fluvoxamine in the Treatment of Non-critically ill Patients with COVID-19: A Living Systematic Review and Meta-analysis
This article has 11 authors:Reviewed by ScreenIT
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High-quality and easy-to-regenerate personal filter
This article has 15 authors:Reviewed by ScreenIT
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SARS-CoV-2 vaccine effectiveness and breakthrough infections in maintenance dialysis patients
This article has 8 authors:Reviewed by ScreenIT
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Increased risk of infection with SARS-CoV-2 Omicron BA.1 compared with Delta in vaccinated and previously infected individuals, the Netherlands, 22 November 2021 to 19 January 2022
This article has 11 authors:Reviewed by ScreenIT
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Randomized Controlled Trial of Early Outpatient COVID-19 Treatment with High-Titer Convalescent Plasma
This article has 58 authors:Reviewed by ScreenIT
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Omicron mutations enhance infectivity and reduce antibody neutralization of SARS-CoV-2 virus-like particles
This article has 21 authors:Reviewed by ScreenIT
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Omicron-Specific Cytotoxic T-Cell Responses After a Third Dose of mRNA COVID-19 Vaccine Among Patients With Multiple Sclerosis Treated With Ocrelizumab
This article has 14 authors:Reviewed by ScreenIT
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Superior immunogenicity and effectiveness of the third compared to the second BNT162b2 vaccine dose
This article has 16 authors:Reviewed by ScreenIT
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Comparative effectiveness of the BNT162b2 and ChAdOx1 vaccines against Covid-19 in people over 50
This article has 6 authors:Reviewed by ScreenIT