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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Vitamin D insufficiency is prevalent in severe COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Characterization of cells susceptible to SARS-COV-2 and methods for detection of neutralizing antibody by focus forming assay
This article has 10 authors:Reviewed by ScreenIT
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Estimating Variation of Covid-19 ‘infection’ in the Population: Results from Understanding Society’s (UKHLS) first monthly covid-19 survey
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 seropositivity and subsequent infection risk in healthy young adults: a prospective cohort study
This article has 35 authors:Reviewed by ScreenIT
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The effect of COVID-19 on critical care research during the first year of the pandemic: A prospective longitudinal multinational survey
This article has 5 authors:Reviewed by ScreenIT
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Impact of essential workers in the context of social distancing for epidemic control
This article has 6 authors:Reviewed by ScreenIT
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Thromboembolic risk in hospitalised and non-hospitalised Covid-19 patients: A self-controlled case series analysis of a nation-wide cohort
This article has 9 authors:Reviewed by ScreenIT
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AI-based analysis of CT images for rapid triage of COVID-19 patients
This article has 12 authors:Reviewed by ScreenIT
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Factors Associated with Good Patient Outcomes Following Convalescent Plasma in COVID-19: A Prospective Phase II Clinical Trial
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases
This article has 19 authors:Reviewed by ScreenIT