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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Evaluating the impact of international airline suspensions on the early global spread of COVID-19
This article has 29 authors:Reviewed by ScreenIT
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Clinical and immunoserological status 12 weeks after infection with COVID-19: prospective observational study
This article has 13 authors:Reviewed by ScreenIT
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Social distancing strategies for curbing the COVID-19 epidemic
This article has 4 authors:Reviewed by ScreenIT
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Longitudinal profiling of respiratory and systemic immune responses reveals myeloid cell-driven lung inflammation in severe COVID-19
This article has 24 authors:Reviewed by ScreenIT
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Estimation and Interactive Visualization of the Time-Varying Reproduction Number R t and the Time-Delay from Infection to Estimation
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 induces double-stranded RNA-mediated innate immune responses in respiratory epithelial-derived cells and cardiomyocytes
This article has 20 authors:Reviewed by ScreenIT
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Development of at-home sample collection logistics for large-scale seroprevalence studies
This article has 10 authors:Reviewed by ScreenIT
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Cell-based Culture Informs Infectivity and Safe De-Isolation Assessments in Patients with Coronavirus Disease 2019
This article has 18 authors:Reviewed by ScreenIT
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A Logistic Formula in Biology and Its Application to Deaths by the Third Wave of COVID-19 in Japan
This article has 2 authors:Reviewed by ScreenIT
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Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases
This article has 9 authors:Reviewed by ScreenIT