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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Clinical validation of engineered CRISPR/Cas12a for rapid SARS-CoV-2 detection
This article has 5 authors:Reviewed by ScreenIT
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Epidemiology Characteristics of COVID-19 Infection Amongst Primary Health Care Workers in Qatar: March-October 2020
This article has 7 authors:Reviewed by ScreenIT
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Effect of co-infection with parasites on severity of COVID-19
This article has 12 authors:Reviewed by ScreenIT
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Predictors of COVID-19 incidence, mortality, and epidemic growth rate at the country level
This article has 3 authors:Reviewed by ScreenIT
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An novel epidemiological model for COVID-19
This article has 1 author:Reviewed by ScreenIT
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Comparison of COVID-19 case and death counts in the United States reported by four online trackers: January 22-May 31, 2020
This article has 1 author:Reviewed by ScreenIT
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Home food procurement impacts food security and diet quality during COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Temporal association between particulate matter pollution and case fatality rate of COVID-19 in Wuhan
This article has 7 authors:Reviewed by ScreenIT
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A model assessing potential benefits of isolation and mass testing on COVID-19: the case of Nigeria
This article has 4 authors:Reviewed by ScreenIT
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Aerial transmission of the SARS-CoV-2 virus through environmental e-cigarette aerosol: implications for public policies
This article has 3 authors:Reviewed by ScreenIT