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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Siltuximab downregulates interleukin-8 and pentraxin 3 to improve ventilatory status and survival in severe COVID-19
This article has 22 authors:Reviewed by ScreenIT
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Parametric analysis of early data on COVID-19 expansion in selected European countries
This article has 1 author:Reviewed by ScreenIT
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A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Japanese citizens' behavioral changes and preparedness against COVID-19: An online survey during the early phase of the pandemic
This article has 5 authors:Reviewed by ScreenIT
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Reporting the life tracks of confirmed cases can effective prevent and control the COVID-19 outbreak in China
This article has 6 authors:Reviewed by ScreenIT
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Clinical manifestations of children with COVID‐19: A systematic review
This article has 5 authors:Reviewed by ScreenIT
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Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK
This article has 8 authors:Reviewed by ScreenIT
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Evaluation of the Anticipated Burden of COVID-19 on Hospital-Based Healthcare Services Across the United States
This article has 5 authors:Reviewed by ScreenIT
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Clinical Features, Diagnosis, and Treatment of COVID-19 in Hospitalized Patients: A Systematic Review of Case Reports and Case Series
This article has 8 authors:Reviewed by ScreenIT
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The QT interval in patients with COVID-19 treated with hydroxychloroquine and azithromycin
This article has 13 authors:Reviewed by ScreenIT