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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Deleterious Effects of SARS-CoV-2 Infection on Human Pancreatic Cells
This article has 11 authors:Reviewed by ScreenIT
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Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment
This article has 2 authors:Reviewed by ScreenIT
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Hypertension delays viral clearance and exacerbates airway hyperinflammation in patients with COVID-19
This article has 38 authors:Reviewed by ScreenIT
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A 5-min RNA preparation method for COVID-19 detection with RT-qPCR
This article has 5 authors:Reviewed by ScreenIT
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Estimating vaccine confidence levels among healthcare students and staff of a tertiary institution in South Africa: protocol of a cross-sectional survey
This article has 4 authors:Reviewed by ScreenIT
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Development of a new aerosol barrier mask for mitigation of spread of SARS-CoV-2 and other infectious pathogens
This article has 8 authors:Reviewed by ScreenIT
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Coronavirus-19 and coagulopathy: A Systematic Review [COVID-COAG]
This article has 8 authors:Reviewed by ScreenIT
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Are mobile phones part of the chain of transmission of SARS-CoV-2 in hospital settings?
This article has 16 authors:Reviewed by ScreenIT
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Health professionals practice and associated factors towards precautionary measures for COVID-19 pandemic in public health facilities of Gamo zone, southern Ethiopia: A cross-sectional study
This article has 8 authors:Reviewed by ScreenIT
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In vivo pharmacokinetic study of remdesivir dry powder for inhalation in hamsters
This article has 8 authors:Reviewed by ScreenIT