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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Who is dying from COVID-19 in the United Kingdom? A review of cremation authorisations from a single South Wales' crematorium
This article has 2 authors:Reviewed by ScreenIT
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Global pattern of COVID-19 research
This article has 8 authors:Reviewed by ScreenIT
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Objective sensory testing methods reveal a higher prevalence of olfactory loss in COVID-19–positive patients compared to subjective methods: A systematic review and meta-analysis
This article has 8 authors:Reviewed by ScreenIT
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Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)
This article has 36 authors:Reviewed by ScreenIT
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Daily Viral Kinetics and Innate and Adaptive Immune Response Assessment in COVID-19: a Case Series
This article has 18 authors:Reviewed by ScreenIT
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Comparison of Two Commercial Platforms and a Laboratory-Developed Test for Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) RNA
This article has 11 authors:Reviewed by ScreenIT
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Foundational research and NIH funding enabling Emergency Use Authorization of remdesivir for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Sample pooling for SARS-CoV-2 RT-PCR screening
This article has 27 authors:Reviewed by ScreenIT
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Prevalence of HIV in patients hospitalized for COVID-19 and associated outcomes: a systematic review and meta-analysis
This article has 7 authors:Reviewed by ScreenIT
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Explainable death toll motion modeling: COVID-19 data-driven narratives
This article has 2 authors:Reviewed by ScreenIT