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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Serum IgA, IgM, and IgG responses in COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Increased PCR screening capacity using a multi-replicate pooling scheme
This article has 5 authors:Reviewed by ScreenIT
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Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource
This article has 6 authors:Reviewed by ScreenIT
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Revealing COVID-19 Transmission by SARS-CoV-2 Genome Sequencing and Agent Based Modelling
This article has 24 authors:Reviewed by ScreenIT
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Distinguishing COVID-19 From Influenza Pneumonia in the Early Stage Through CT Imaging and Clinical Features
This article has 14 authors:Reviewed by ScreenIT
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Effectiveness and safety of glucocorticoids to treat COVID-19: a rapid review and meta-analysis
This article has 19 authors:Reviewed by ScreenIT
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Interleukin-6 blockade for severe COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Utah-Stanford Ventilator (Vent4US): Developing a rapidly scalable ventilator for COVID-19 patients with ARDS
This article has 14 authors: -
The Contribution of Age Structure to the Number of Deaths from Covid-19 in the UK by Geographical Units
This article has 2 authors:Reviewed by ScreenIT
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Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19
This article has 11 authors:Reviewed by ScreenIT