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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Activation of the SARS-CoV-2 receptor Ace2 by cytokines through pan JAK-STAT enhancers
This article has 2 authors:Reviewed by ScreenIT
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Rapid isolation of potent SARS-CoV-2 neutralizing antibodies and protection in a small animal model
This article has 30 authors:Reviewed by ScreenIT
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Evidence for strong mutation bias towards, and selection against, T/U content in SARS-CoV2: implications for attenuated vaccine design
This article has 10 authors:Reviewed by ScreenIT
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A Rapid, Cost-Effective Tailed Amplicon Method for Sequencing SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review
This article has 22 authors:Reviewed by ScreenIT
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Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China
This article has 5 authors:Reviewed by ScreenIT
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High estradiol and low testosterone levels are associated with critical illness in male but not in female COVID-19 patients: a retrospective cohort study
This article has 25 authors:Reviewed by ScreenIT
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THE COVID-19 FORECAST IN NORTHWEST SYRIA: The Imperative of Global Action to Avoid Catastrophe
This article has 5 authors:Reviewed by ScreenIT
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Hydroxychloroquine for the treatment of COVID-19: the importance of scrutiny of positive trials
This article has 3 authors:Reviewed by ScreenIT
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Associations with covid-19 hospitalisation amongst 406,793 adults: the UK Biobank prospective cohort study
This article has 9 authors:Reviewed by ScreenIT