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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County-Specific, Real-Time Projection of the Effect of Business Closures on the COVID-19 Pandemic
This article has 2 authors:Reviewed by ScreenIT
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Decline in mitigation readiness facilitated second waves of SARS-CoV-2
This article has 1 author:Reviewed by ScreenIT
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Screening plans for SARS-CoV-2 based on sampling and rotation: An example in a European school setting
This article has 2 authors:Reviewed by ScreenIT
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A robust phenomenological approach to investigate COVID-19 data for France
This article has 3 authors:Reviewed by ScreenIT
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Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people
This article has 10 authors:Reviewed by ScreenIT
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Correcting excess mortality for pandemic-associated population decreases
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 and Influenza: Vaccination Before and During the Pandemic among the Lebanese Adult Population
This article has 3 authors:Reviewed by ScreenIT
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Efficacy of the ChAdOx1 nCoV-19 Covid-19 Vaccine against the B.1.351 Variant
This article has 51 authors:Reviewed by ScreenIT, Rapid Reviews Infectious Diseases
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Seroprevalence of SARS-CoV-2, Symptom Profiles and Sero-Neutralization in a Suburban Area, France
This article has 8 authors:Reviewed by ScreenIT
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Quantifying the preventive effect of wearing face masks
This article has 1 author:Reviewed by ScreenIT