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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Intra-Host SARS-CoV-2 Evolution in the Gut of Mucosally-Infected Chlorocebus aethiops (African Green Monkeys)
This article has 8 authors:Reviewed by ScreenIT
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Anti-PF4 levels of patients with VITT do not reduce 4 months following AZD1222 vaccination
This article has 9 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Improving the reproduction number calculation by treating for daily variations of SARS-CoV-2 cases
This article has 3 authors:Reviewed by ScreenIT
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Pediatric critical COVID-19 and mortality in a multinational cohort
This article has 12 authors:Reviewed by ScreenIT
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The impact on the mental health and well-being of unpaid carers affected by social distancing, self-isolation and shielding during the COVID 19 pandemic in England – a systematic review
This article has 3 authors:Reviewed by ScreenIT
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Predicting SARS-CoV-2 infections for children and youth with single symptom screening
This article has 7 authors:Reviewed by ScreenIT
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The SARS-CoV-2 Delta variant is poised to acquire complete resistance to wild-type spike vaccines
This article has 24 authors:Reviewed by ScreenIT
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Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples
This article has 9 authors:Reviewed by ScreenIT
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Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, or thrombocytopenic events: A population-based cohort study of 46 million adults in England
This article has 16 authors:Reviewed by ScreenIT
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Gene-Environment Interaction Analysis Incorporating Sex, Cardiometabolic Diseases, and Multiple Deprivation Index Reveals Novel Genetic Associations With COVID-19 Severity
This article has 6 authors:Reviewed by ScreenIT