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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COVID-19 related outcomes for hospitalised older people at risk of frailty
This article has 7 authors:Reviewed by ScreenIT
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Massively scaled-up testing for SARS-CoV-2 RNA via next-generation sequencing of pooled and barcoded nasal and saliva samples
This article has 41 authors:Reviewed by ScreenIT
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Determinants of expression of SARS‐CoV‐2 entry‐related genes in upper and lower airways
This article has 37 authors:Reviewed by ScreenIT
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Quantitative Method for Comparative Assessment of Particle Removal Efficiency of Fabric Masks as Alternatives to Standard Surgical Masks for PPE
This article has 5 authors:Reviewed by ScreenIT
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A double-edged sword—telemedicine for maternal care during COVID-19: findings from a global mixed-methods study of healthcare providers
This article has 9 authors:Reviewed by ScreenIT
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Impact of COVID-19 on care-home mortality and life expectancy in Scotland
This article has 11 authors:Reviewed by ScreenIT
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Delays, Masks, the Elderly, and Schools: First Covid-19 Wave in the Czech Republic
This article has 13 authors:Reviewed by ScreenIT
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SARS-CoV-2 Viral Load in Saliva Rises Gradually and to Moderate Levels in Some Humans
This article has 14 authors:Reviewed by ScreenIT
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Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection
This article has 9 authors:Reviewed by ScreenIT
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How Social Engagement Against Covid-19 in a Brazilian Slum Helped Mitigate Rising Statistics
This article has 12 authors:Reviewed by ScreenIT