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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SARS-CoV-2 Variant Exposures Elicit Antibody Responses With Differential Cross-Neutralization of Established and Emerging Strains Including Delta and Omicron
This article has 17 authors:Reviewed by ScreenIT
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Four-week forecasts of COVID-19 epidemic trajectories in South Africa, Chile, Peru and Brazil: a model evaluation
This article has 7 authors:Reviewed by ScreenIT
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Combined Impact of Prior SARS-CoV-2 Infection and Vaccination on Antibody Presence
This article has 7 authors:Reviewed by ScreenIT
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pH-dependent polymorphism of the structure of SARS-CoV-2 nsp7
This article has 7 authors:Reviewed by ScreenIT
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Immune recall improves antibody durability and breadth to SARS-CoV-2 variants
This article has 15 authors:Reviewed by ScreenIT
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mRNA vaccination in octogenarians 15 and 20 months after recovery from COVID-19 elicits robust immune and antibody responses that include Omicron
This article has 12 authors:Reviewed by ScreenIT
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Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States
This article has 20 authors:Reviewed by ScreenIT
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A randomized controlled trial of inhaled ciclesonide for outpatient treatment of symptomatic COVID-19 infections
This article has 7 authors:Reviewed by ScreenIT
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An Open Label, Adaptive, Phase 1 Trial of High‐Dose Oral Nitazoxanide in Healthy Volunteers: An Antiviral Candidate for SARS‐CoV‐2
This article has 34 authors:Reviewed by ScreenIT
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ANTICIPATING RACIAL/ETHNIC MORTALITY DISPLACEMENT FROM COVID-19
This article has 2 authors:Reviewed by ScreenIT