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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SARS-CoV-2 D614 and G614 spike variants impair neuronal synapses and exhibit differential fusion ability
This article has 3 authors:Reviewed by ScreenIT
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Emerging SARS-CoV-2 Diversity Revealed by Rapid Whole-Genome Sequence Typing
This article has 2 authors:Reviewed by ScreenIT
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Mortality among Adults Ages 25-44 in the United States During the COVID-19 Pandemic
This article has 6 authors:Reviewed by ScreenIT
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Susceptibility of swine cells and domestic pigs to SARS-CoV-2
This article has 15 authors:Reviewed by ScreenIT
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Mutational signatures in countries affected by SARS-CoV-2: Implications in host-pathogen interactome
This article has 4 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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First indication of the effect of COVID-19 vaccinations on the course of the outbreak in Israel
This article has 5 authors:Reviewed by ScreenIT
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The SARS-CoV-2 and other human coronavirus spike proteins are fine-tuned towards temperature and proteases of the human airways
This article has 13 authors:Reviewed by ScreenIT
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Phase I/II study of COVID-19 RNA vaccine BNT162b1 in adults
This article has 25 authors:Reviewed by ScreenIT
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Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study
This article has 5 authors:Reviewed by ScreenIT
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Adverse outcomes in COVID-19 and diabetes: a retrospective cohort study from three London teaching hospitals
This article has 26 authors:Reviewed by ScreenIT