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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Novel gene-specific translation mechanism of dysregulated, chronic inflammation reveals promising, multifaceted COVID-19 therapeutics
This article has 20 authors:Reviewed by ScreenIT
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Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique
This article has 6 authors:Reviewed by ScreenIT
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Distinct Patterns of Emergence of SARS-CoV-2 Spike Variants including N501Y in Clinical Samples in Columbus Ohio
This article has 11 authors:Reviewed by ScreenIT
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Challenges for targeting SARS-CoV-2 proteases as a therapeutic strategy for COVID-19
This article has 15 authors:Reviewed by ScreenIT
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Green spaces mitigate racial disparity of health: A higher ratio of green spaces indicates a lower racial disparity in SARS-CoV-2 infection rates in the USA
This article has 8 authors:Reviewed by ScreenIT
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Public health information on COVID-19 for international travellers: lessons learned from a mixed-method evaluation
This article has 13 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 during pregnancy and associated outcomes: Results from an ongoing prospective cohort
This article has 23 authors:Reviewed by ScreenIT
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Peripheral innate and adaptive immune cells during COVID ‐19: Functional neutrophils, pro‐inflammatory monocytes, and half‐dead lymphocytes
This article has 9 authors:Reviewed by ScreenIT
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High-risk exposure without personal protective equipment and infection with SARS-CoV-2 in-hospital workers - The CoV-CONTACT cohort
This article has 207 authors:Reviewed by ScreenIT
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Differences in innate Intracellular viral suppression competencies may explain variations in morbidity and mortality from SARS-CoV-2 infection
This article has 5 authors:Reviewed by ScreenIT