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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Predictive modeling of COVID-19 case growth highlights evolving racial and ethnic risk factors in Tennessee and Georgia
This article has 4 authors:Reviewed by ScreenIT
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Extracellular vesicle-based vaccine platform displaying native viral envelope proteins elicits a robust anti-SARS-CoV-2 response in mice
This article has 8 authors:Reviewed by ScreenIT
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Overweight/obesity as the potentially most important lifestyle factor associated with signs of pneumonia in COVID-19
This article has 11 authors:Reviewed by ScreenIT
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The development of Nanosota-1 as anti-SARS-CoV-2 nanobody drug candidates
This article has 15 authors:Reviewed by ScreenIT
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Tropism of SARS-CoV-2 for Developing Human Cortical Astrocytes
This article has 14 authors:Reviewed by ScreenIT
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Public Views about COVID-19 “Immunity Passports”
This article has 2 authors:Reviewed by ScreenIT
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The Conundrum of Giglio Island: unraveling the dynamics of an apparent resistance to COVID-19 – A descriptive study
This article has 19 authors:Reviewed by ScreenIT
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When it is available, will we take it? Social media users’ perception of hypothetical COVID-19 vaccine in Nigeria
This article has 5 authors:Reviewed by ScreenIT
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The Application of Sample Pooling for Mass Screening of SARS-CoV-2 in an Outbreak of COVID-19 in Vietnam
This article has 19 authors:Reviewed by ScreenIT
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Integrative analyses identify susceptibility genes underlying COVID-19 hospitalization
This article has 15 authors:Reviewed by ScreenIT