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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Modelling Singapore COVID-19 pandemic with a SEIR multiplex network model
This article has 2 authors:Reviewed by ScreenIT
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Forecasting the peak of novel coronavirus disease in Egypt using current confirmed cases and deaths
This article has 2 authors:Reviewed by ScreenIT
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Incidence and risk factors of kidney impairment on patients with COVID-19: A meta-analysis of 10180 patients
This article has 2 authors:Reviewed by ScreenIT
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Uncertainty quantification in epidemiological models for the COVID-19 pandemic
This article has 3 authors:Reviewed by ScreenIT
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Impact of social media on knowledge dissemination between physicians during COVID-19 virus outbreak: A cross sectional survey
This article has 4 authors:Reviewed by ScreenIT
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The Role of Host Genetic Factors in Coronavirus Susceptibility: Review of Animal and Systematic Review of Human Literature
This article has 5 authors:Reviewed by ScreenIT
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Development and application of Pandemic Projection Measures (PPM) for forecasting the COVID-19 outbreak
This article has 1 author:Reviewed by ScreenIT
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COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification
This article has 5 authors:Reviewed by ScreenIT
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Preliminary detection of lung hypoperfusion in discharged Covid-19 patients during recovery
This article has 7 authors:Reviewed by ScreenIT
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Concordance of “rapid” serological tests and IgG and IgM chemiluminescence for SARS-COV-2
This article has 2 authors:Reviewed by ScreenIT