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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Copper(II) Gluconate Boosts the Anti-SARS-CoV-2 Effect of Disulfiram In Vitro
This article has 6 authors:Reviewed by ScreenIT
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Predominance of Distinct Autoantibodies in Response to SARS-CoV-2 Infection
This article has 19 authors:Reviewed by ScreenIT
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COVID-19 vaccine effectiveness against hospitalizations and ICU admissions in the Netherlands, April- August 2021
This article has 13 authors: -
Disparate impacts on online information access during the Covid-19 pandemic
This article has 4 authors:Reviewed by ScreenIT
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Comparison of UK paediatric SARS-CoV-2 admissions across the first and second pandemic waves
This article has 26 authors:Reviewed by ScreenIT
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A novel hamster model of SARS-CoV-2 respiratory infection using a pseudotyped virus
This article has 10 authors:Reviewed by ScreenIT
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Hospital-level work organization drives the spread of SARS-CoV-2 within hospitals: insights from a multi-ward model
This article has 6 authors:Reviewed by ScreenIT
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Women's views and experiences of accessing pertussis vaccination in pregnancy and infant vaccinations during the COVID-19 pandemic: A multi-methods study in the UK
This article has 6 authors:Reviewed by ScreenIT
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Seroresponse to SARS-CoV-2 Vaccines among Maintenance Dialysis Patients over 6 Months
This article has 14 authors:Reviewed by ScreenIT
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A Genetic Trap in Yeast for Inhibitors of SARS-CoV-2 Main Protease
This article has 7 authors:Reviewed by ScreenIT