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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Comparison of serum neurodegenerative biomarkers among hospitalized COVID‐19 patients versus non‐COVID subjects with normal cognition, mild cognitive impairment, or Alzheimer's dementia
This article has 14 authors:Reviewed by ScreenIT
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A Transnational and Transregional Study of the Impact and Effectiveness of Social Distancing for COVID-19 Mitigation
This article has 3 authors:Reviewed by ScreenIT
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The genetics of eating behaviors: research in the age of COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Effectiveness of inactivated COVID-19 vaccines against severe illness in B.1.617.2 (Delta) variant–infected patients in Jiangsu, China
This article has 10 authors:Reviewed by ScreenIT
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No difference in risk of hospitalization between reported cases of the SARS-CoV-2 Delta variant and Alpha variant in Norway
This article has 13 authors:Reviewed by ScreenIT
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MITIGATING THE 4 th WAVE OF THE COVID-19 PANDEMIC IN ONTARIO
This article has 3 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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The impact of mental health and substance use issues on COVID-19 vaccine readiness: a cross sectional community-based survey in Ontario, Canada
This article has 10 authors:Reviewed by ScreenIT
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Whole genome sequencing identifies multiple loci for critical illness caused by COVID-19
This article has 62 authors:Reviewed by ScreenIT
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The COVID-19 Pandemic and Ophthalmic Care: A Qualitative Study of Patients with Neovascular Age-Related Macular Degeneration (nAMD)
This article has 17 authors:Reviewed by ScreenIT