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 Neutralizing Activity of mRNA-1273 against SARS-CoV-2 Variants
This article has 12 authors:Reviewed by ScreenIT
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Taiwan on track to end third COVID-19 community outbreak
This article has 2 authors:Reviewed by ScreenIT
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Early warning signal reliability varies with COVID-19 waves
This article has 2 authors:Reviewed by ScreenIT
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Monitoring SARS-CoV-2 Populations in Wastewater by Amplicon Sequencing and Using the Novel Program SAM Refiner
This article has 5 authors:Reviewed by ScreenIT
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A Cross-Sectional Study of the Relationship Between Exercise, Physical Activity, and Health-Related Quality of Life Among Japanese Workers
This article has 9 authors:Reviewed by ScreenIT
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Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity
This article has 20 authors:Reviewed by ScreenIT
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SARS-CoV-2 Variants Are Selecting for Spike Protein Mutations That Increase Protein Stability
This article has 2 authors: -
Evaluation of the effectiveness of remdesivir in severe COVID-19 using observational data from a prospective national cohort study
This article has 10 authors:Reviewed by ScreenIT
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Temporal Analysis of Social Determinants Associated with COVID-19 Mortality
This article has 3 authors:Reviewed by ScreenIT
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Drug repurposing based on a Quantum-Inspired method versus classical fingerprinting uncovers potential antivirals against SARS-CoV-2 including vitamin B12
This article has 12 authors:Reviewed by ScreenIT