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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Systematic investigations of COVID-19 in 283 cancer patients
This article has 45 authors:Reviewed by ScreenIT
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COVID-19 infections and outcomes in a live registry of heart failure patients across an integrated health care system
This article has 16 authors:Reviewed by ScreenIT
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Incidence of COVID-19 and Connections with Air Pollution Exposure: Evidence from the Netherlands
This article has 1 author:Reviewed by ScreenIT
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Estimation of Viral Aerosol Emissions From Simulated Individuals With Asymptomatic to Moderate Coronavirus Disease 2019
This article has 2 authors:Reviewed by ScreenIT
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Artificial Intelligence for Rapid Meta-Analysis: Case Study on Ocular Toxicity of Hydroxychloroquine
This article has 6 authors:Reviewed by ScreenIT
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How 3D printing and social media tackles the PPE shortage during Covid – 19 pandemic
This article has 7 authors:Reviewed by ScreenIT
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Predictive value of sudden olfactory loss in the diagnosis of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Releasing the lockdown in the UK Covid-19 epidemic: a stochastic model
This article has 1 author:Reviewed by ScreenIT
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Quantitative Estimation of Disruption in Social Contact Structure and its Effect in COVID-19 Spread in India
This article has 2 authors:Reviewed by ScreenIT
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Variation among states in rate of coronavirus spread
This article has 1 author:Reviewed by ScreenIT