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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Structural and metabolic brain abnormalities in COVID-19 patients with sudden loss of smell
This article has 12 authors:Reviewed by ScreenIT
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Weather, Social Distancing, and the Spread of COVID-19 *
This article has 1 author:Reviewed by ScreenIT
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Antihypertensive medications and COVID‐19 diagnosis and mortality: Population‐based case‐control analysis in the United Kingdom
This article has 4 authors:Reviewed by ScreenIT
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Planning phase two for endoscopic units in Northern Italy after the COVID-19 lockdown: An exit strategy with a lot of critical issues and a few opportunities
This article has 6 authors:Reviewed by ScreenIT
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Modeling the initial phase of SARS-CoV-2 deposition in the respiratory tract mimicked by the 11C radionuclide
This article has 9 authors:Reviewed by ScreenIT
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Intense and Mild Wave of COVID-19 in The Gambia: a Cohort Analysis
This article has 2 authors:Reviewed by ScreenIT
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Potential health and economic impacts of dexamethasone treatment for patients with COVID-19
This article has 88 authors:Reviewed by ScreenIT
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Biochemical, biophysical, and immunological characterization of respiratory secretions in severe SARS-CoV-2 infections
This article has 27 authors:Reviewed by ScreenIT
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Extended SEIQR type model for COVID-19 epidemic and data analysis
This article has 3 authors:Reviewed by ScreenIT
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The incubation period of COVID-19: A scoping review and meta-analysis to aid modelling and planning
This article has 2 authors:Reviewed by ScreenIT