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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Postacute sequelae and adaptive immune responses in people with HIV recovering from SARS-COV-2 infection
This article has 32 authors:Reviewed by ScreenIT
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Folic acid and methotrexate use and their association with COVID-19 diagnosis and mortality: a case–control analysis from the UK Biobank
This article has 6 authors:Reviewed by ScreenIT
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Next-generation intranasal Covid-19 vaccine: a polymersome-based protein subunit formulation that provides robust protection against multiple variants of concern and early reduction in viral load of the upper airway in the golden Syrian hamster model
This article has 11 authors:Reviewed by ScreenIT
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Quantifying political influence on COVID-19 fatality in Brazil
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Permissive glioblastoma cell line for high throughput antiviral screening
This article has 7 authors:Reviewed by ScreenIT
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Risk of severe COVID-19 in patients with inflammatory rheumatic diseases treated with immunosuppressive therapy in Scotland
This article has 6 authors:Reviewed by ScreenIT
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Unpacking COVID ‐19 and conspiracy theories in the UK black community
This article has 5 authors:Reviewed by ScreenIT
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Persistence, prevalence, and polymorphism of sequelae after COVID-19 in unvaccinated, young adults of the Swiss Armed Forces: a longitudinal, cohort study (LoCoMo)
This article has 9 authors:Reviewed by ScreenIT
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COVID-19 in Japan, January–March 2020: insights from the first three months of the epidemic
This article has 8 authors:Reviewed by ScreenIT
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Empirical evidence of transmission over a school-household network for SARS-CoV-2; exploration of transmission pairs stratified by primary and secondary school
This article has 7 authors:Reviewed by ScreenIT