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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SARS-CoV-2 lineage B.6 was the major contributor to early pandemic transmission in Malaysia
This article has 11 authors:Reviewed by ScreenIT
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Deep RNA sequencing of intensive care unit patients with COVID-19
This article has 13 authors:Reviewed by ScreenIT
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Risk factors for severe disease in patients admitted with COVID-19 to a hospital in London, England: a retrospective cohort study
This article has 7 authors:Reviewed by ScreenIT
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Model to Describe Fast Shutoff of CoVID-19 Pandemic Spread
This article has 1 author:Reviewed by ScreenIT
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Optimally pooled viral testing
This article has 1 author:Reviewed by ScreenIT
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COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates
This article has 1 author:Reviewed by ScreenIT
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Comparison of Time to Clinical Improvement With vs Without Remdesivir Treatment in Hospitalized Patients With COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review
This article has 14 authors:Reviewed by ScreenIT
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Strategic release of lockdowns in a COVID infection model
This article has 3 authors:Reviewed by ScreenIT
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A Statistical Model for Quantifying the Needed Duration of Social Distancing for the COVID-19 Pandemic
This article has 4 authors:Reviewed by ScreenIT