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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Estimating COVID-19 under-reporting across 86 nations: implications for projections and control
This article has 3 authors:Reviewed by ScreenIT
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Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA
This article has 2 authors:Reviewed by ScreenIT
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Novel coronavirus (COVID-19) Outbreak in Iraq: The First Wave and Future Scenario
This article has 4 authors:Reviewed by ScreenIT
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Exploring Causal relationship between risk factors and vulnerability to COVID-19 Cases of Italy, Spain, France, Greece, Portugal, Morocco and South Africa
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 related concerns of people with long-term respiratory conditions: a qualitative study
This article has 6 authors:Reviewed by ScreenIT
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Mathematical modeling of the COVID-19 prevalence in Saudi Arabia
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 seroprevalence among hospital staff and preprocedural patients in Thai community hospitals: a cross-sectional study
This article has 4 authors:Reviewed by ScreenIT
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Excess of cardiovascular deaths during the COVID-19 pandemic in Brazilian capital cities
This article has 7 authors:Reviewed by ScreenIT
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Persistence of viral RNA, pneumocyte syncytia and thrombosis are hallmarks of advanced COVID-19 pathology
This article has 13 authors:Reviewed by ScreenIT
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Treatment of ARDS and hyperinflammation in COVID-19 with IL-6 antagonist Tocilizumab: a tertiary care experience from Pakistan
This article has 5 authors:Reviewed by ScreenIT