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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COVID-19 Pandemic Impact on Sexually Transmitted Infection Testing in a College Setting
This article has 4 authors:Reviewed by ScreenIT
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COVIDNearTerm: A simple method to forecast COVID-19 hospitalizations
This article has 11 authors:Reviewed by ScreenIT
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Non-invasive diagnostic method to objectively measure olfaction and diagnose smell disorders by molecularly targeted fluorescent imaging agent
This article has 17 authors:Reviewed by ScreenIT
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Alphavirus infection triggers selective cytoplasmic translocation of nuclear RBPs with moonlighting antiviral roles
This article has 18 authors:Reviewed by ScreenIT
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Nine-month presence of SARS-CoV-2 in saliva: a case report
This article has 2 authors:Reviewed by ScreenIT
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Estimate of the rate of unreported COVID-19 cases during the first outbreak in Rio de Janeiro
This article has 3 authors:Reviewed by ScreenIT
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Covid-19 Vaccine Effectiveness in New York State
This article has 12 authors:Reviewed by ScreenIT
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Comprehensive antibody profiling of mRNA vaccination in children
This article has 18 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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A bacteria-based assay to study SARS-CoV-2 protein-protein interactions
This article has 4 authors:Reviewed by ScreenIT
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RETRACTED AND REPLACED: Taste loss as a distinct symptom of COVID-19: a systematic review and meta-analysis
This article has 9 authors:Reviewed by ScreenIT