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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Down regulation of defensin genes during SARS-CoV-2 infection
This article has 4 authors:Reviewed by ScreenIT
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Precision shielding for COVID-19: metrics of assessment and feasibility of deployment
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 shedding dynamics across the respiratory tract, sex, and disease severity for adult and pediatric COVID-19
This article has 6 authors:This article has been curated by 1 group: -
Higher Temperature, Pressure, and Ultraviolet Are Associated With Less COVID-19 Prevalence: Meta-Regression of Japanese Prefectural Data
This article has 7 authors:Reviewed by ScreenIT
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Acute Demyelinating Encephalomyelitis (ADEM) in COVID-19 infection: A Case Series
This article has 4 authors:Reviewed by ScreenIT
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Probabilistic approaches for classifying highly variable anti-SARS-CoV-2 antibody responses
This article has 27 authors:Reviewed by ScreenIT
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A proof of concept for neutralizing antibody-guided vaccine design against SARS-CoV-2
This article has 27 authors:Reviewed by ScreenIT
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COVID-19 Case Mortality Rates Continue to Decline in Florida
This article has 1 author:Reviewed by ScreenIT
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Simple Ventilators for Emergency Use Based on Bag-Valve Pressing Systems: Lessons Learned and Future Steps
This article has 19 authors:Reviewed by ScreenIT
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Impact Analysis of SARS-CoV2 on Signaling Pathways during COVID19 Pathogenesis using Codon Usage Assisted Host-Viral Protein Interactions
This article has 3 authors:Reviewed by ScreenIT