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 unique evolutionary dynamics of the SARS-CoV-2 Delta variant
This article has 10 authors:Reviewed by ScreenIT
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Systematic review protocol exploring the impact of the COVID-19 pandemic on the wellbeing of general practitioners
This article has 6 authors:Reviewed by ScreenIT
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Learning torus PCA based classification for multiscale RNA backbone structure correction with application to SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
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Reduction in preterm birth rates during and after the COVID ‐19 lockdown in Queensland Australia
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 antibody changes in patients receiving COVID-19 convalescent plasma from normal and vaccinated donors
This article has 8 authors:Reviewed by ScreenIT
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Elapsed time since BNT162b2 vaccine and risk of SARS-CoV-2 infection: test negative design study
This article has 9 authors: -
Serendipitous COVID-19 Vaccine-Mix in Uttar Pradesh, India: Safety and Immunogenicity Assessment of a Heterologous Regime
This article has 16 authors:Reviewed by ScreenIT
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RIG-I-induced innate antiviral immunity protects mice from lethal SARS-CoV-2 infection
This article has 8 authors:Reviewed by ScreenIT
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Challenges in Tracking the Risk of COVID-19 in Bangladesh: Evaluation of A Novel Method
This article has 5 authors:Reviewed by ScreenIT
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Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: an analysis of facebook data
This article has 5 authors:Reviewed by ScreenIT