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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Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed −1 ribosomal frameshifting
This article has 8 authors:Reviewed by ScreenIT
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The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK
This article has 29 authors:Reviewed by ScreenIT
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Usefulness of real-time RT-PCR to understand the kinetics of SARS-CoV-2 in blood: A prospective study
This article has 8 authors:Reviewed by ScreenIT
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“Pandemic of the unvaccinated”? At midlife, white people are less vaccinated but still at less risk of Covid-19 mortality in Minnesota
This article has 4 authors:Reviewed by ScreenIT
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Post-COVID-19 condition 3 months after hospitalisation with SARS-CoV-2 in South Africa: a prospective cohort study
This article has 16 authors:Reviewed by ScreenIT
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Anti-Spike Antibody Response to Natural Infection with SARS-CoV-2 and Its Activity against Emerging Variants
This article has 8 authors:Reviewed by ScreenIT
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Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations
This article has 21 authors:Reviewed by ScreenIT
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Culture and identification of a “Deltamicron” SARS‐CoV‐2 in a three cases cluster in southern France
This article has 12 authors:Reviewed by ScreenIT
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Quantifying the immunological distinctiveness of emerging SARS-CoV-2 variants in the context of prior regional herd exposure
This article has 9 authors:Reviewed by ScreenIT
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Intragenomic rearrangements in SARS-CoV-2, other betacoronaviruses, and alphacoronaviruses
This article has 2 authors:Reviewed by ScreenIT