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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Empirical non-linear modeling & forecast of global daily deaths of COVID-19 pandemic & evidence that a “third wave” is beginning to decay
This article has 1 author:Reviewed by ScreenIT
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A study on the effects of containment policies and vaccination on the spread of SARS-CoV-2
This article has 1 author:Reviewed by ScreenIT
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Cyclic 68 Ga-Labeled Peptides for Specific Detection of Human Angiotensin-Converting Enzyme 2
This article has 6 authors:Reviewed by ScreenIT
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Identification of a Super-Spreading Chain of Transmission Associated with COVID-19 at the Early Stage of the Disease Outbreak in Wuhan
This article has 21 authors:Reviewed by ScreenIT
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Battling the COVID-19 Pandemic: Is Bangladesh Prepared?
This article has 3 authors:Reviewed by ScreenIT
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Saliva Alternative to Upper Respiratory Swabs for SARS-CoV-2 Diagnosis
This article has 20 authors:Reviewed by ScreenIT
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Sex and age bias viral burden and interferon responses during SARS-CoV-2 infection in ferrets
This article has 17 authors:Reviewed by ScreenIT
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Can age-distribution be an indicator of the goodness of COVID-19 testing?
This article has 3 authors:Reviewed by ScreenIT
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Novel Machine-Learned Approach for COVID-19 Resource Allocation: A Tool for Evaluating Community Susceptibility
This article has 1 author:Reviewed by ScreenIT
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Evaluation of three rapid lateral flow antigen detection tests for the diagnosis of SARS-CoV-2 infection
This article has 9 authors:Reviewed by ScreenIT