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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Durability of Protection Post–Primary COVID-19 Vaccination in the United States
This article has 12 authors:Reviewed by ScreenIT
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Protection against the Omicron Variant from Previous SARS-CoV-2 Infection
This article has 26 authors:Reviewed by ScreenIT
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Updated projections for COVID-19 omicron wave in Florida
This article has 3 authors:Reviewed by ScreenIT
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Evaluating real-world COVID-19 vaccine effectiveness using a test-negative case–control design
This article has 9 authors:Reviewed by ScreenIT
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Association between BNT162b2 vaccination and reported incidence of post-COVID-19 symptoms: cross-sectional study 2020-21, Israel
This article has 10 authors:Reviewed by ScreenIT
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Data-Driven Assessment of Adolescents’ Mental Health During the COVID-19 Pandemic
This article has 12 authors:Reviewed by ScreenIT
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Adherence of SARS-CoV-2 Delta Variant to a Surgical Mask and N95 Respirators
This article has 3 authors:Reviewed by ScreenIT
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The Impact of Vaccination on Incidence and Outcomes of SARS-CoV-2 Infection in Patients with Kidney Failure in Scotland
This article has 20 authors:Reviewed by ScreenIT
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A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort
This article has 5 authors:Reviewed by ScreenIT
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Effect of vaccination on household transmission of SARS-CoV-2 Delta variant of concern
This article has 13 authors:Reviewed by ScreenIT