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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Quantifying Absolute Neutralization Titers against SARS-CoV-2 by a Standardized Virus Neutralization Assay Allows for Cross-Cohort Comparisons of COVID-19 Sera
This article has 32 authors:Reviewed by ScreenIT
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Structural genetics of circulating variants affecting the SARS-CoV-2 spike/human ACE2 complex
This article has 4 authors:Reviewed by ScreenIT
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Vascular Thrombosis in COVID-19: A Potential Association with Antiphospholipid Antibodies
This article has 3 authors:Reviewed by ScreenIT
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Designing Efficient Contact Tracing Through Risk-Based Quarantining
This article has 5 authors:Reviewed by ScreenIT
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Testing Healthcare Workers Exposed to COVID19 using Rapid Antigen Detection
This article has 7 authors:Reviewed by ScreenIT
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Age differential analysis of COVID-19 second wave in Europe reveals highest incidence among young adults
This article has 2 authors:Reviewed by ScreenIT
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Initial Model for USA CoVID-19 Resurgence
This article has 1 author:Reviewed by ScreenIT
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Viruses such as SARS-CoV-2 can be partially shielded from UV radiation when in particles generated by sneezing or coughing: Numerical simulations
This article has 3 authors:Reviewed by ScreenIT
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Structure-Guided Mutagenesis Alters Deubiquitinating Activity and Attenuates Pathogenesis of a Murine Coronavirus
This article has 10 authors:Reviewed by ScreenIT
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Lockdown, relaxation, and acme period in COVID-19: A study of disease dynamics in Hermosillo, Sonora, Mexico
This article has 7 authors:Reviewed by ScreenIT