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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Corticosteroids are associated with increased survival in elderly presenting severe SARS-Cov2 infection
This article has 8 authors:Reviewed by ScreenIT
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Implementing a telemedicine curriculum for internal medicine residents during a pandemic: the Cleveland Clinic experience
This article has 10 authors:Reviewed by ScreenIT
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Adverse effects of remdesivir, hydroxychloroquine and lopinavir/ritonavir when used for COVID-19: systematic review and meta-analysis of randomised trials
This article has 15 authors:Reviewed by ScreenIT
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Clinical and laboratory evaluation of patients with SARS-CoV-2 pneumonia treated with high-titer convalescent plasma
This article has 48 authors:Reviewed by ScreenIT
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Norwich COVID-19 testing initiative pilot: evaluating the feasibility of asymptomatic testing on a university campus
This article has 25 authors:Reviewed by ScreenIT
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SARS-CoV-2 Impairs Dendritic Cells and Regulates DC-SIGN Gene Expression in Tissues
This article has 14 authors:Reviewed by ScreenIT
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SARS‐CoV2 antigen in whole mouth fluid may be a reliable rapid detection tool
This article has 12 authors:Reviewed by ScreenIT
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Clinical characteristics and outcomes of COVID-19 patients with diabetes mellitus in Kuwait
This article has 12 authors:Reviewed by ScreenIT
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A SARS-CoV-2 – host proximity interactome
This article has 18 authors:Reviewed by ScreenIT
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Factors associated with SARS-CoV-2 infection and outbreaks in long-term care facilities in England: a national cross-sectional survey
This article has 11 authors:Reviewed by ScreenIT