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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Predictive performance of international COVID-19 mortality forecasting models
This article has 13 authors:Reviewed by ScreenIT
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Mathematical Modeling Based Study and Prediction of COVID-19 Epidemic Dissemination Under the Impact of Lockdown in India
This article has 3 authors:Reviewed by ScreenIT
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Representative estimates of COVID-19 infection fatality rates from four locations in India: cross-sectional study
This article has 5 authors:Reviewed by ScreenIT
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Visuospatial processing impairment following mild COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Modeling the Spread and Control of COVID-19
This article has 3 authors:Reviewed by ScreenIT
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A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Modeling the COVID-19 dissemination in the South Region of Brazil and testing gradual mitigation strategies
This article has 1 author:Reviewed by ScreenIT
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Cardiovascular-related deaths at the beginning of the COVID-19 outbreak: a prospective analysis based on the UK Biobank
This article has 10 authors:Reviewed by ScreenIT
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Practical considerations for Ultraviolet-C radiation mediated decontamination of N95 respirator against SARS-CoV-2 virus
This article has 13 authors:Reviewed by ScreenIT
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PI3K/mTOR and topoisomerase inhibitors with potential activity against SARS-CoV-2 infection
This article has 6 authors:Reviewed by ScreenIT