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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Transmission of COVID-19 in the state of Georgia, United States: Spatiotemporal variation and impact of social distancing
This article has 9 authors:Reviewed by ScreenIT
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Effectiveness of non-pharmaceutical interventions to contain COVID-19: a case study of the 2020 spring pandemic wave in New York City
This article has 3 authors: -
COVID-19 Quarantine Reveals Grade-specific Behavioral Modification of Myopia: One-Million Chinese Schoolchildren Study
This article has 21 authors:Reviewed by ScreenIT
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The global impact of the first Coronavirus Disease 2019 (COVID-19) pandemic wave on vascular services
This article has 3 authors:Reviewed by ScreenIT
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Association between use of Qingfei Paidu Tang and mortality in hospitalized patients with COVID-19: A national retrospective registry study
This article has 16 authors:Reviewed by ScreenIT
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Performance of fabrics for home-made masks against the spread of COVID-19 through droplets: A quantitative mechanistic study
This article has 6 authors:Reviewed by ScreenIT
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Assessing the plausibility of supercritical transmission for an emerging or re-emerging pathogen
This article has 4 authors:Reviewed by ScreenIT
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PREDICTORS OF UPTAKE OF A POTENTIAL COVID-19 VACCINE AMONG NIGERIAN ADULTS
This article has 15 authors:Reviewed by ScreenIT
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Sentinel Event Surveillance to Estimate Total Sars-CoV-2 Infections, United States
This article has 2 authors:Reviewed by ScreenIT
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Genomic Diversity of the SARS-CoV-2 in Turkey and the Impact of Virus Genome Mutations on Clinical Outcomes
This article has 16 authors:Reviewed by ScreenIT