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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Prevalence of SARS-CoV-2 in Household Members and Other Close Contacts of COVID-19 Cases: A Serologic Study in Canton of Vaud, Switzerland
This article has 18 authors:Reviewed by ScreenIT
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REACT-1 round 6 updated report: high prevalence of SARS-CoV-2 swab positivity with reduced rate of growth in England at the start of November 2020
This article has 15 authors:Reviewed by ScreenIT
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The effects of hypertension as an existing comorbidity on mortality rate in patients with COVID-19 A systematic review and meta-analysis
This article has 1 author:Reviewed by ScreenIT
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Communicating personalized risks from COVID-19: guidelines from an empirical study
This article has 9 authors:Reviewed by ScreenIT
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An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility
This article has 16 authors:Reviewed by ScreenIT
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On Machine Learning-Based Short-Term Adjustment of Epidemiological Projections of COVID-19 in US
This article has 12 authors:Reviewed by ScreenIT
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Estimation of the fraction of COVID-19 infected people in U.S. states and countries worldwide
This article has 2 authors:Reviewed by ScreenIT
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A cross-sectional study of socioeconomic status and treatment interruption among Japanese workers during the COVID-19 pandemic
This article has 10 authors:Reviewed by ScreenIT
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Impact assessment of full and partial stay-at-home orders, face mask usage, and contact tracing: An agent-based simulation study of COVID-19 for an urban region
This article has 3 authors:Reviewed by ScreenIT
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Evaluating the sensitivity of SARS-CoV-2 infection rates on college campuses to wastewater surveillance
This article has 8 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT