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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Optimizing direct RT-LAMP to detect transmissible SARS-CoV-2 from primary nasopharyngeal swab samples
This article has 10 authors:Reviewed by ScreenIT
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Exploring dynamics and network analysis of spike glycoprotein of SARS-COV-2
This article has 3 authors:Reviewed by ScreenIT
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Model Based Comparison of Covid-19 Cases in Two Counties in the Silicon Valley
This article has 1 author:Reviewed by ScreenIT
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A longitudinal study of the impact of university student return to campus on the SARS-CoV-2 seroprevalence among the community members
This article has 14 authors:Reviewed by ScreenIT
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Rapid Review of SARS-CoV-1 and SARS-CoV-2 Viability, Susceptibility to Treatment, and the Disinfection and Reuse of PPE, Particularly Filtering Facepiece Respirators
This article has 4 authors:Reviewed by ScreenIT
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Severe underestimation of COVID-19 case numbers: effect of epidemic growth rate and test restrictions
This article has 1 author:Reviewed by ScreenIT
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Modeling the Epidemic Trend of the 2019 Novel Coronavirus Outbreak in China
This article has 4 authors:Reviewed by ScreenIT
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Evaluating the Need for Routine COVID-19 Testing of Emergency Department Staff: Quantitative Analysis
This article has 2 authors:Reviewed by ScreenIT
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Interest in COVID-19 vaccine trials participation among young adults in China: Willingness, reasons for hesitancy, and demographic and psychosocial determinants
This article has 3 authors:Reviewed by ScreenIT
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Detection Of Genomic Variants Of SARS-CoV-2 Circulating In Wastewater By High-Throughput Sequencing
This article has 11 authors:Reviewed by ScreenIT