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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Limited SARS-CoV-2 diversity within hosts and following passage in cell culture
This article has 11 authors:Reviewed by ScreenIT
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Exceptional diversity and selection pressure on SARS-CoV and SARS-CoV-2 host receptor in bats compared to other mammals
This article has 3 authors:Reviewed by ScreenIT
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Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2 viral replication by targeting the viral main protease
This article has 11 authors:Reviewed by ScreenIT
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Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
This article has 8 authors:Reviewed by ScreenIT
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Estimating COVID-19 outbreak risk through air travel
This article has 3 authors:Reviewed by ScreenIT
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Heparin Therapy Improving Hypoxia in COVID-19 Patients – A Case Series
This article has 8 authors:Reviewed by ScreenIT
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Temporal Detection and Phylogenetic Assessment of SARS-CoV-2 in Municipal Wastewater
This article has 9 authors:Reviewed by ScreenIT
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TOWARD A COVID-19 SCORE-RISK ASSESSMENTS AND REGISTRY
This article has 7 authors:Reviewed by ScreenIT
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Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study
This article has 15 authors:Reviewed by ScreenIT
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Modeling quarantine during epidemics and mass-testing using drones
This article has 3 authors:Reviewed by ScreenIT