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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Personal protective equipment for reducing the risk of COVID-19 infection among healthcare workers involved in emergency trauma surgery during the pandemic: an umbrella review protocol
This article has 5 authors:Reviewed by ScreenIT
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Quantifying Effects, Forecasting Releases, and Herd Immunity of the Covid-19 Epidemic in S. Paulo – Brazil
This article has 1 author:Reviewed by ScreenIT
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Rapid, Sensitive and High-Throughput Screening Method for Detection of SARS-Cov-2 Antibodies by Bio-Layer Interferometry
This article has 7 authors:Reviewed by ScreenIT
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Globally Coherent Weekly Periodicity in the Covid-19 Pandemic
This article has 1 author:Reviewed by ScreenIT
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Estimates of the rate of infection and asymptomatic COVID-19 disease in a population sample from SE England
This article has 31 authors:Reviewed by ScreenIT
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Short‐term neuropsychiatric outcomes and quality of life in COVID‐19 survivors
This article has 15 authors:Reviewed by ScreenIT
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A delayed modulation of solar ultraviolet radiation on the COVID ‐19 transmission reflects an incubation period
This article has 5 authors:Reviewed by ScreenIT
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Transmission dynamics reveal the impracticality of COVID-19 herd immunity strategies
This article has 2 authors:Reviewed by ScreenIT
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QFEA - A Method for Assessing the Filtration Efficiency of Face Mask Materials for Early Design Prototypes and Home Mask Makers
This article has 6 authors:Reviewed by ScreenIT
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In vitro efficacy of Artemisinin-based treatments against SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT