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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Sudden hyposmia as a prevalent symptom of COVID-19 infection
This article has 5 authors:Reviewed by ScreenIT
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Clinical characteristics of COVID-19 infection in pregnant women: a systematic review and meta-analysis
This article has 7 authors:Reviewed by ScreenIT
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Management of rheumatic diseases in the time of covid-19 pandemic: perspectives of rheumatology practitioners from India
This article has 5 authors:Reviewed by ScreenIT
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The phenotypic changes of γδ T cells in COVID‐19 patients
This article has 13 authors:Reviewed by ScreenIT
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A Systematic Meta-Analysis of CT Features of COVID-19: Lessons from Radiology
This article has 7 authors:Reviewed by ScreenIT
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Efficient and Practical Sample Pooling for High-Throughput PCR Diagnosis of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Real-time tracking of self-reported symptoms to predict potential COVID-19
This article has 20 authors:Reviewed by ScreenIT
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Statistical methods for batch screening of input populations by stage and group in COVID-19 nucleic acid testing
This article has 1 author:Reviewed by ScreenIT
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COVID-19: Metaheuristic Optimization-Based Forecast Method on Time-Dependent Bootstrapped Data
This article has 2 authors:Reviewed by ScreenIT
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Toilets dominate environmental detection of severe acute respiratory syndrome coronavirus 2 in a hospital
This article has 16 authors:Reviewed by ScreenIT