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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Hydroxychloroquine in mild-to-moderate coronavirus disease 2019: a placebo-controlled double blind trial
This article has 182 authors:Reviewed by ScreenIT
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The Relationships of Deteriorating Depression and Anxiety With Longitudinal Behavioral Changes in Google and YouTube Use During COVID-19: Observational Study
This article has 5 authors:Reviewed by ScreenIT
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Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan
This article has 6 authors:Reviewed by ScreenIT
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What association do political interventions, environmental and health variables have with the number of Covid-19 cases and deaths? A linear modeling approach
This article has 2 authors:Reviewed by ScreenIT
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Early versus deferred anti-SARS-CoV-2 convalescent plasma in patients admitted for COVID-19: A randomized phase II clinical trial
This article has 32 authors:Reviewed by ScreenIT
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Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform
This article has 37 authors:Reviewed by ScreenIT
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An Evolutionary Portrait of the Progenitor SARS-CoV-2 and Its Dominant Offshoots in COVID-19 Pandemic
This article has 8 authors:Reviewed by ScreenIT
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The impact of the coronavirus disease 2019 (COVID-19) outbreak on cancer practice in Japan: using an administrative database
This article has 9 authors:Reviewed by ScreenIT
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Genetic mechanisms of critical illness in COVID-19
This article has 72 authors:Reviewed by ScreenIT
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A systematic review and meta-analysis of pregnancy and COVID-19: Signs and symptoms, laboratory tests, and perinatal outcomes
This article has 8 authors:Reviewed by ScreenIT