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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Hospital saturation and risk of death without receiving mechanical ventilation in hospitalized COVID-19 patients: a city-wide analysis
This article has 2 authors:Reviewed by ScreenIT
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A New Saliva-Based Lateral-Flow SARS-CoV-2 IgG Antibody Test for mRNA Vaccination
This article has 16 authors:Reviewed by ScreenIT
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Phosphatidylserine receptors enhance SARS-CoV-2 infection
This article has 18 authors:Reviewed by ScreenIT
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Antibody Responses to SARS-CoV-2 After Infection or Vaccination in Children and Young Adults With Inflammatory Bowel Disease
This article has 14 authors:Reviewed by ScreenIT
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Assessing the Level and Determinants of COVID-19 Vaccine Confidence in Kenya
This article has 8 authors:Reviewed by ScreenIT
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Structural Modeling of the TMPRSS Subfamily of Host Cell Proteases Reveals Potential Binding Sites
This article has 3 authors:Reviewed by ScreenIT
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Interferon-stimulated and metallothionein-expressing macrophages are associated with acute and chronic allograft dysfunction after lung transplantation
This article has 12 authors:Reviewed by ScreenIT
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A phase I trial of cyclosporine for hospitalized patients with COVID-19
This article has 23 authors:Reviewed by ScreenIT
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Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020—March 2021) Using a Statistical Learning Strategy
This article has 10 authors:Reviewed by ScreenIT
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Impact of long-term care facilities’ size on adherence to COVID-19’ infection prevention guidance
This article has 4 authors:Reviewed by ScreenIT