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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An alpaca nanobody neutralizes SARS-CoV-2 by blocking receptor interaction
This article has 12 authors:Reviewed by ScreenIT
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Structural basis for neutralization of SARS-CoV-2 and SARS-CoV by a potent therapeutic antibody
This article has 23 authors:Reviewed by ScreenIT
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Clinical features of COVID-19 patients in Abdul Wahab Sjahranie Hospital, Samarinda, Indonesia
This article has 5 authors:Reviewed by ScreenIT
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SCALE19: A scalable and cost-efficient method for testing Covid-19 based on hierarchical group testing
This article has 3 authors:Reviewed by ScreenIT
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Breath-, air- and surface-borne SARS-CoV-2 in hospitals
This article has 24 authors:Reviewed by ScreenIT
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Association Between Nonsteroidal Antiinflammatory Drug Use and Adverse Clinical Outcomes Among Adults Hospitalized With Coronavirus 2019 in South Korea: A Nationwide Study
This article has 6 authors:Reviewed by ScreenIT
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Feeling Positive About Reopening? New Normal Scenarios from COVID-19 Reopen Sentiment Analytics
This article has 7 authors:Reviewed by ScreenIT
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Public Knowledge and Practices Regarding Coronavirus Disease 2019: A Cross-Sectional Survey From Pakistan
This article has 8 authors:Reviewed by ScreenIT
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Predictors to Use Mobile Apps for Monitoring COVID-19 Symptoms and Contact Tracing: Survey Among Dutch Citizens
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 in Environmental Samples of Quarantined Households
This article has 15 authors:Reviewed by ScreenIT