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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Diet quality and risk and severity of COVID-19: a prospective cohort study
This article has 30 authors:Reviewed by ScreenIT
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A physically plausible incidence rate for compartmental epidemiological models
This article has 1 author:Reviewed by ScreenIT
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Testing & Opening in Augustusburg A Success Story?
This article has 4 authors:Reviewed by ScreenIT
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Selective tweeting of COVID-19 articles: Does title or abstract positivity influence dissemination?
This article has 10 authors:Reviewed by ScreenIT
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Evaluation of the Panbio ™ rapid antigen test for COVID-19 diagnosis in symptomatic health care workers
This article has 5 authors:Reviewed by ScreenIT
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Modelling, Simulations and Analysis of the First COVID-19 Epidemic in Shanghai
This article has 1 author:Reviewed by ScreenIT
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The Influence of Public Health Faculty on College and University Plans During the COVID-19 Pandemic
This article has 5 authors:Reviewed by ScreenIT
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Impact of COVID-19 on deaths from respiratory diseases: Panel data evidence from Chile
This article has 4 authors:Reviewed by ScreenIT
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Prior sleep-wake behaviors are associated with mental health outcomes during the COVID-19 pandemic among adult users of a wearable device in the United States
This article has 6 authors:Reviewed by ScreenIT
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The Impact of Legislation on Covid-19 Mortality in a Brazilian Federative Unit was Mediated by Social Isolation
This article has 6 authors:Reviewed by ScreenIT