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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Proteomic Profiling in Biracial Cohorts Implicates DC-SIGN as a Mediator of Genetic Risk in COVID-19
This article has 22 authors:Reviewed by ScreenIT
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Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
This article has 36 authors:Reviewed by ScreenIT
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Initial whole-genome sequencing and analysis of the host genetic contribution to COVID-19 severity and susceptibility
This article has 27 authors:Reviewed by ScreenIT
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What does and does not correlate with COVID-19 death rates
This article has 2 authors:Reviewed by ScreenIT
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Impact of COVID ‐19 pandemic on lung cancer treatment scheduling
This article has 6 authors:Reviewed by ScreenIT
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Implications of the reverse associations between obesity prevalence and coronavirus disease (COVID-19) cases and related deaths in the United States
This article has 3 authors:Reviewed by ScreenIT
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Changes in Solo and Partnered Sexual Behaviors during the COVID-19 Pandemic: Findings from a U.S. Probability Survey
This article has 5 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 nucleocapsid protein phase‐separates with RNA and with human hnRNPs
This article has 6 authors:Reviewed by ScreenIT
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Age-Dependent Progression of SARS-CoV-2 Infection in Syrian Hamsters
This article has 10 authors:Reviewed by ScreenIT
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Global cataloguing of variations in untranslated regions of viral genome and prediction of key host RNA binding protein-microRNA interactions modulating genome stability in SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT