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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Ultra-rapid detection of SARS-CoV-2 in public workspace environments
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection and COVID-19 severity in individuals with prior seasonal coronavirus infection
This article has 9 authors:Reviewed by ScreenIT
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Genomic Feature Analysis of Betacoronavirus Provides Insights Into SARS and COVID-19 Pandemics
This article has 10 authors:Reviewed by ScreenIT
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Analysis of COVID-19 spread in South Korea using the SIR model with time-dependent parameters and deep learning
This article has 4 authors:Reviewed by ScreenIT
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Virtual Handover of Patients in the Pediatric Intensive Care Unit During the Covid-19 Crisis
This article has 15 authors:Reviewed by ScreenIT
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Prediction of the coronavirus epidemic prevalence in quarantine conditions based on an approximate calculation model
This article has 2 authors:Reviewed by ScreenIT
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Apparent reductions in COVID-19 Case Fatality Rates reflect changes in average age of those testing positive
This article has 1 author:Reviewed by ScreenIT
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Disinfection of Stethoscope and Non-Infrared Thermometer: Practices of Physicians in Ethiopia in the Era of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on remote mental healthcare and prescribing in psychiatry: an electronic health record study
This article has 10 authors:Reviewed by ScreenIT
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A sensitive, simple, and low-cost method for COVID-19 wastewater surveillance at an institutional level
This article has 8 authors:Reviewed by ScreenIT