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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The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA-supertype-dependent manner
This article has 16 authors:Reviewed by ScreenIT
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The Female-Predominant Persistent Immune Dysregulation of the Post-COVID Syndrome
This article has 15 authors:Reviewed by ScreenIT
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Immune responses against SARS-CoV-2 variants after heterologous and homologous ChAdOx1 nCoV-19/BNT162b2 vaccination
This article has 25 authors:Reviewed by ScreenIT
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Immunological dysfunction persists for 8 months following initial mild-to-moderate SARS-CoV-2 infection
This article has 12 authors:Reviewed by ScreenIT
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Variant-of-concern-attributable health and health system-related outcomes: a population-level propensity-score matched cohort study
This article has 6 authors:Reviewed by ScreenIT
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CD4 + T cell lymphopenia and dysfunction in severe COVID-19 disease is autocrine TNF-α/TNFRI-dependent
This article has 34 authors:Reviewed by ScreenIT
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Implementing Mandatory Testing and a Public Health Commitment to Control COVID-19 on a College Campus
This article has 5 authors:Reviewed by ScreenIT
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The COVID-19 pandemic storm in India subsides, but the calm is still far away
This article has 1 author:Reviewed by ScreenIT
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Pathogenic neutrophilia drives acute respiratory distress syndrome in severe COVID-19 patients
This article has 19 authors:Reviewed by ScreenIT
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Minimum Manufacturing Costs, National Prices, and Estimated Global Availability of New Repurposed Therapies for Coronavirus Disease 2019
This article has 4 authors:Reviewed by ScreenIT