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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Filtration Performance Degradation of In‐Use Masks by Vapors from Alcohol‐Based Hand Sanitizers and the Mitigation Solutions
This article has 5 authors:Reviewed by ScreenIT
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Sex-based clinical and immunological differences in COVID-19
This article has 18 authors:Reviewed by ScreenIT
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Transmission of SARS-CoV-2 considering shared chairs in outpatient dialysis: a real-world case-control study
This article has 13 authors: -
Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil
This article has 10 authors:Reviewed by ScreenIT
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Colchicine for community-treated patients with COVID-19 (COLCORONA): a phase 3, randomised, double-blinded, adaptive, placebo-controlled, multicentre trial
This article has 44 authors:Reviewed by ScreenIT
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Genetic predispositions to psychiatric disorders and the risk of COVID-19
This article has 14 authors:Reviewed by ScreenIT
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Daytime variation in SARS-CoV-2 infection and cytokine production
This article has 6 authors:Reviewed by ScreenIT
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Recent Randomized Trials of Antithrombotic Therapy for Patients With COVID-19
This article has 27 authors:Reviewed by ScreenIT
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Impact of SARS-CoV-2 pandemic among health care workers in a secondary teaching hospital in Spain
This article has 19 authors:Reviewed by ScreenIT
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A comparative study of infection and mortality in COVID-19 across countries: A scaling analysis
This article has 8 authors:Reviewed by ScreenIT