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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Possible transmission flow of SARS-CoV-2 based on ACE2 features
This article has 24 authors:Reviewed by ScreenIT
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Modelling the transmission of infectious diseases inside hospital bays: implications for Covid-19
This article has 3 authors:Reviewed by ScreenIT
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Effect of Renin-Angiotensin-Aldosterone System inhibitors on outcomes of COVID-19 patients with hypertension: Systematic review and Meta-analysis
This article has 3 authors:Reviewed by ScreenIT
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A booster dose enhances immunogenicity of the COVID-19 vaccine candidate ChAdOx1 nCoV-19 in aged mice
This article has 19 authors:Reviewed by ScreenIT
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They’re Dying in the Suburbs: COVID-19 Cases and Deaths by Geography in Louisiana (USA)
This article has 2 authors:Reviewed by ScreenIT
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A privacy-preserving Bayesian network model for personalised COVID19 risk assessment and contact tracing
This article has 8 authors:Reviewed by ScreenIT
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PUBLIC TRANSIT RIDERSHIP ANALYSIS DURING THE COVID-19 PANDEMIC
This article has 3 authors:Reviewed by ScreenIT
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Evaluation of commercially available immuno‐magnetic agglutination in comparison to enzyme‐linked immunosorbent assays for rapid point‐of‐care diagnostics of COVID‐19
This article has 10 authors:Reviewed by ScreenIT
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Plasma tissue plasminogen activator and plasminogen activator inhibitor-1 in hospitalized COVID-19 patients
This article has 10 authors:Reviewed by ScreenIT
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Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada
This article has 3 authors:Reviewed by ScreenIT