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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High-Potency Polypeptide-based Inhibition of Enveloped-virus Glycoproteins
This article has 3 authors:Reviewed by ScreenIT
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Distinct Metabolic Profile Associated with a Fatal Outcome in COVID-19 Patients during the Early Epidemic in Italy
This article has 24 authors:Reviewed by ScreenIT
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A multiplexed high-throughput neutralization assay reveals a lack of activity against multiple variants after SARS-CoV-2 infection
This article has 10 authors:Reviewed by ScreenIT
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A high rate of COVID-19 vaccine hesitancy in a large-scale survey on Arabs
This article has 4 authors:Reviewed by ScreenIT
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Epidemiology and transmission of COVID-19 in cases and close contacts in Georgia in the first four months of the epidemic
This article has 14 authors:Reviewed by ScreenIT
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High SARS-CoV-2 attack rates following exposure during five singing events in the Netherlands, September-October 2020
This article has 8 authors:Reviewed by ScreenIT
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Graphical Models of Pandemic
This article has 8 authors:Reviewed by ScreenIT
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Disparate temperature-dependent virus–host dynamics for SARS-CoV-2 and SARS-CoV in the human respiratory epithelium
This article has 22 authors:Reviewed by ScreenIT
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The risk factors of COVID-19 in a longitudinal population-based study
This article has 6 authors:Reviewed by ScreenIT
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An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis
This article has 16 authors:Reviewed by GigaScience, ScreenIT