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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Disentangling Increased Testing from Covid-19 Epidemic Spread
This article has 4 authors:Reviewed by ScreenIT
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Mobility data can explain the entire COVID-19 outbreak course in Japan
This article has 3 authors:Reviewed by ScreenIT
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Social and psychiatric effects of Covid-19 pandemic and distance learning on high school students: A cross-sectional web-based survey
This article has 2 authors:Reviewed by ScreenIT
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Intention to have the seasonal influenza vaccination during the COVID-19 pandemic among eligible adults in the UK: a cross-sectional survey
This article has 8 authors:Reviewed by ScreenIT
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On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate
This article has 4 authors:Reviewed by ScreenIT
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Strengthening government’s response to COVID-19 in Indonesia: A modified Delphi study of medical and health academics
This article has 3 authors:Reviewed by ScreenIT
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Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China
This article has 7 authors:Reviewed by ScreenIT
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Changes in the behavioural determinants of health during the COVID-19 pandemic: gender, socioeconomic and ethnic inequalities in five British cohort studies
This article has 7 authors:Reviewed by ScreenIT
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Positive outcomes associated with the COVID‐19 pandemic in Australia
This article has 11 authors:Reviewed by ScreenIT
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Novel Ionophores Active against La Crosse Virus Identified through Rapid Antiviral Screening
This article has 6 authors:Reviewed by ScreenIT