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 Impact of the first COVID-19 shelter-in-place announcement on social distancing, difficulty in daily activities, and levels of concern in the San Francisco Bay Area: A cross-sectional social media survey
This article has 8 authors:Reviewed by ScreenIT
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Male gender and kidney illness are associated with an increased risk of severe laboratory-confirmed coronavirus disease
This article has 5 authors:Reviewed by ScreenIT
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Comparison of different anticoagulation strategies for renal replacement therapy in critically ill patients with COVID-19: a cohort study
This article has 8 authors:Reviewed by ScreenIT
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Pseudo-likelihood based logistic regression for estimating COVID-19 infection and case fatality rates by gender, race, and age in California
This article has 9 authors:Reviewed by ScreenIT
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Standard operating procedures for SARS-CoV-2 detection by a clinical diagnostic RT-LAMP assay
Reviewed by ScreenIT
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A highly effective reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay for the rapid detection of SARS-CoV-2 infection
This article has 28 authors:Reviewed by ScreenIT
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Modelling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike glycoprotein vaccine candidate NVX-CoV2373 immunogenicity in baboons and protection in mice
This article has 30 authors:Reviewed by ScreenIT
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A glycan cluster on the SARS-CoV-2 spike ectodomain is recognized by Fab-dimerized glycan-reactive antibodies
This article has 17 authors:Reviewed by ScreenIT
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Mutations derived from horseshoe bat ACE2 orthologs enhance ACE2-Fc neutralization of SARS-CoV-2
This article has 18 authors:Reviewed by ScreenIT