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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A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties
This article has 12 authors:Reviewed by ScreenIT
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Dynamic Estimation of Epidemiological Parameters of Covid-19 Outbreak and Effects of Interventions on Its Spread
This article has 7 authors:Reviewed by ScreenIT
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Building an international consortium for tracking coronavirus health status
This article has 53 authors:Reviewed by ScreenIT
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Global expansion of COVID-19 pandemic is driven by population size and airport connections
This article has 8 authors:Reviewed by ScreenIT
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Therapeutic management of patients with COVID-19: a systematic review
This article has 7 authors:Reviewed by ScreenIT
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Perceived vulnerability to COVID-19 infection from event attendance: results from Louisiana, USA, two weeks preceding the national emergency declaration
This article has 8 authors:Reviewed by ScreenIT
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Widespread use of face masks in public may slow the spread of SARS CoV-2: an ecological study
This article has 1 author:Reviewed by ScreenIT
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Patient-collected tongue, nasal, and mid-turbinate swabs for SARS-CoV-2 yield equivalent sensitivity to health care worker collected nasopharyngeal swabs
This article has 9 authors:Reviewed by ScreenIT
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Cryptic transmission of SARS-CoV-2 in Washington state
This article has 88 authors:Reviewed by ScreenIT
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Rapid implementation of mobile technology for real-time epidemiology of COVID-19
This article has 73 authors:Reviewed by ScreenIT