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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Relationship between COVID-19 death toll doubling time and national BCG vaccination policy
This article has 2 authors:Reviewed by ScreenIT
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An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK
This article has 2 authors:Reviewed by ScreenIT
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Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19
This article has 19 authors:Reviewed by ScreenIT
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Quarantine fatigue thins fat-tailed coronavirus impacts in U.S. cities by making epidemics inevitable
This article has 3 authors:Reviewed by ScreenIT
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The optimal allocation of Covid-19 vaccines
This article has 3 authors:Reviewed by ScreenIT
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Dynamics of ORF1ab and N Gene among hospitalized COVID-19 positive cohorts: A hospital based retrospective study
This article has 11 authors:Reviewed by ScreenIT
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Presence of SARS-Coronavirus-2 RNA in Sewage and Correlation with Reported COVID-19 Prevalence in the Early Stage of the Epidemic in The Netherlands
This article has 5 authors:Reviewed by ScreenIT
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Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis
This article has 4 authors:Reviewed by ScreenIT
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Estimating Cumulative COVID-19 Infections by a Novel “Pandemic Rate Equation”
This article has 1 author:Reviewed by ScreenIT
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A Digital Survey on the Acceptance and Affordability of COVID 19 Vaccine among the People of West Bengal, India- A Survey Based Study
This article has 14 authors:Reviewed by ScreenIT