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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Infection and mortality of healthcare workers worldwide from COVID-19: a systematic review
This article has 64 authors:Reviewed by ScreenIT
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Dynamics of COVID-19 under social distancing measures are driven by transmission network structure
This article has 5 authors:Reviewed by ScreenIT
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Detection of SARs-CoV-2 in wastewater using the existing environmental surveillance network: A potential supplementary system for monitoring COVID-19 transmission
This article has 27 authors:Reviewed by ScreenIT
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Extended use or reuse of single-use surgical masks and filtering face-piece respirators during the coronavirus disease 2019 (COVID-19) pandemic: A rapid systematic review
This article has 12 authors:Reviewed by ScreenIT
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Mechanical ventilation utilization in COVID-19: A systematic review and meta-analysis
This article has 8 authors:Reviewed by ScreenIT
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A tertiary center experience of multiple myeloma patients with COVID-19: lessons learned and the path forward
This article has 13 authors:Reviewed by ScreenIT
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The impact of occupational risk from COVID on GP supply in England: A cross-sectional study
This article has 2 authors:Reviewed by ScreenIT
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Understanding the impact of the COVID-19 pandemic on well-being and virtual care for people living with dementia and care partners living in the community
This article has 10 authors:Reviewed by ScreenIT
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Psychological and situational profiles of social distance compliance during COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Tocilizumab reduces the risk of ICU admission and mortality in patients with SARS-CoV-2 infection
This article has 41 authors:Reviewed by ScreenIT