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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Face Mask Use in the Community for Reducing the Spread of COVID-19: A Systematic Review
This article has 13 authors:Reviewed by ScreenIT
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Abnormal antibodies to self-carbohydrates in SARS-CoV-2-infected patients
This article has 24 authors:Reviewed by ScreenIT
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SARS-CoV-2 infections in 165 countries over time
This article has 1 author:Reviewed by ScreenIT
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Gout, Rheumatoid Arthritis, and the Risk of Death Related to Coronavirus Disease 2019: An Analysis of the UK Biobank
This article has 7 authors:Reviewed by ScreenIT
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Twitter Engagement of U.S. Psychiatry Residency Programs with Black Lives Matter and Coronavirus Disease 2019 (COVID-19)
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 in Japan: What could happen in the future?
This article has 20 authors:Reviewed by ScreenIT
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Ozone exposure upregulates the expression of host susceptibility protein TMPRSS2 to SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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High incidence of venous thrombosis in patients with moderate-to-severe COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study
This article has 7 authors:Reviewed by ScreenIT
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Evaluation of COVID-19 RT-qPCR Test in Multi sample Pools
This article has 16 authors:Reviewed by ScreenIT