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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Early outcomes in adults hospitalized with severe SARS-CoV-2 infection receiving tocilizumab
This article has 17 authors:Reviewed by ScreenIT
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Compassionate drug (mis)use during pandemics: lessons for COVID-19 from 2009
This article has 3 authors:Reviewed by ScreenIT
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Clinical course and risk factors for recurrence of positive SARS-CoV-2 RNA: a retrospective cohort study from Wuhan, China
This article has 13 authors:Reviewed by ScreenIT
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British Thoracic Society survey of rehabilitation to support recovery of the post-COVID-19 population
This article has 7 authors:Reviewed by ScreenIT
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Capsid integrity quantitative PCR to determine virus infectivity in environmental and food applications – A systematic review
This article has 7 authors:Reviewed by ScreenIT
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SELF-POLICING COVID-19 AND CIVIC RESPONSIBILITIES IN LAGOS METROPOLIS, NIGERIA
This article has 1 author:Reviewed by ScreenIT
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Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation
This article has 8 authors:Reviewed by ScreenIT
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Evolving Transmission Network Dynamics of COVID-19 Cluster Infections in South Korea: a descriptive study
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 outbreak, social response, and early economic effects: a global VAR analysis of cross-country interdependencies
This article has 1 author:Reviewed by ScreenIT
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Genetic Drift Versus Climate Region Spreading Dynamics of COVID-19
This article has 4 authors:Reviewed by ScreenIT