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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Occupational exposures and programmatic response to COVID-19 pandemic: an emergency medical services experience
This article has 15 authors:Reviewed by ScreenIT
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Why are most COVID-19 infection curves linear?
This article has 3 authors:Reviewed by ScreenIT
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C-Reactive protein and SOFA scale: A simple score as early predictor of critical care requirement in patients with COVID-19 pneumonia in Spain
This article has 7 authors:Reviewed by ScreenIT
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Severe Acute Respiratory Syndrome Coronavirus 2 Lethality Did not Change Over Time in Two Italian Provinces
This article has 8 authors:Reviewed by ScreenIT
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A systems approach to inflammation identifies therapeutic targets in SARS-CoV-2 infection
This article has 39 authors:Reviewed by ScreenIT
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Modelling the impact of plasma therapy and immunotherapy for recovery of COVID-19 infected individuals
This article has 5 authors:Reviewed by ScreenIT
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Visualizing the COVID-19 pandemic in Bangladesh using coxcombs: A tribute to Florence Nightingale
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 Pandemic with Human Mobility Across Countries
This article has 3 authors:Reviewed by ScreenIT
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The estimations of the COVID-19 incubation period: A scoping reviews of the literature
This article has 2 authors:Reviewed by ScreenIT
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Spatial and temporal dynamics of SARS-CoV-2 in COVID-19 patients: A systematic review and meta-analysis
This article has 3 authors:Reviewed by ScreenIT