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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The Hyperlipidaemic Drug Fenofibrate Significantly Reduces Infection by SARS-CoV-2 in Cell Culture Models
This article has 16 authors:Reviewed by ScreenIT
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Modelling the impact of COVID-19-related programme interruptions on visceral leishmaniasis in India
This article has 4 authors:Reviewed by ScreenIT
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A retrospective cohort study of risk factors for mortality among nursing homes exposed to COVID-19 in Spain
This article has 20 authors:Reviewed by ScreenIT
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Structural basis of fitness of emerging SARS-COV-2 variants and considerations for screening, testing and surveillance strategy to contain their threat
This article has 3 authors:Reviewed by ScreenIT
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Understanding the asymmetric spread and case fatality rate (CFR) for COVID-19 among countries
This article has 2 authors:Reviewed by ScreenIT
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Lethality of SARS-CoV-2 infection in K18 human angiotensin-converting enzyme 2 transgenic mice
This article has 42 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on the mental health and well-being of adults with mental health conditions in the UK: a qualitative interview study
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 in US Youth Soccer Athletes During Summer 2020
This article has 6 authors:Reviewed by ScreenIT
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High variability in transmission of SARS-CoV-2 within households and implications for control
This article has 10 authors:Reviewed by ScreenIT
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Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus in Fall 2020
This article has 16 authors:Reviewed by ScreenIT