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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From Multiplex Serology to Serolomics—A Novel Approach to the Antibody Response against the SARS-CoV-2 Proteome
This article has 15 authors:Reviewed by ScreenIT
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A comparison of Remdesivir versus Au 22 Glutathione 18 in COVID-19 golden hamsters: a better therapeutic outcome of gold compound
This article has 22 authors:Reviewed by ScreenIT
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COVID-19 incidence trends between April and June 2020: A global analysis
This article has 2 authors:Reviewed by ScreenIT
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The use of health geography modeling to understand early dispersion of COVID-19 in São Paulo, Brazil
This article has 7 authors:Reviewed by ScreenIT
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Predicting the impact of asymptomatic transmission, non-pharmaceutical intervention and testing on the spread of COVID19
This article has 4 authors:Reviewed by ScreenIT
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Lean Ad hoc Extracorporeal Membrane Oxygenation Systems for COVID-19
This article has 2 authors:Reviewed by ScreenIT
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National routine adult immunisation programmes among World Health Organization Member States: an assessment of health systems to deploy COVID-19 vaccines
This article has 6 authors:Reviewed by ScreenIT
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Effect of COVID-19 on Critical ICU Capacity in US Acute Care Hospitals
This article has 3 authors:Reviewed by ScreenIT
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SARS-CoV-2 viroporin triggers the NLRP3 inflammatory pathway
This article has 7 authors:Reviewed by ScreenIT
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Why the SARS-CoV-2 antibody test results may be misleading: insights from a longitudinal analysis of COVID-19
This article has 6 authors:Reviewed by ScreenIT