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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Single-cell RNA sequencing of blood antigen-presenting cells in severe COVID-19 reveals multi-process defects in antiviral immunity
This article has 13 authors:Reviewed by ScreenIT
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Positivity of SARS-CoV-2, by RT-PCR among workers of a Public Hospital in the city of Santos, SP, Brazil 2020
This article has 5 authors:Reviewed by ScreenIT
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Enhanced SARS-CoV-2 Neutralization by Secretory IgA in vitro
This article has 20 authors:Reviewed by ScreenIT
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Evidence of SARS-CoV2 entry protein ACE2 in the human nose and olfactory bulb
This article has 8 authors:Reviewed by ScreenIT
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Effective contact tracing for COVID-19: A systematic review
This article has 5 authors:Reviewed by ScreenIT
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Extraction-free RT-LAMP to detect SARS-CoV-2 is less sensitive but highly specific compared to standard RT-PCR in 101 samples
This article has 3 authors:Reviewed by ScreenIT
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Prediction of the COVID-19 epidemic trends based on SEIR and AI models
This article has 5 authors:Reviewed by ScreenIT
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Assessment of Multiplex Digital Droplet RT-PCR as a Diagnostic Tool for SARS-CoV-2 Detection in Nasopharyngeal Swabs and Saliva Samples
This article has 13 authors:Reviewed by ScreenIT
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Mortality in COVID-19 among women on hormone replacement therapy: a retrospective cohort study
This article has 6 authors:Reviewed by ScreenIT
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PHYSICIANS REACTIONS TO COVID 19.THE RESULTS OF A PRELIMINARY INTERNATIONAL INTERNET SURVEY
This article has 14 authors:Reviewed by ScreenIT