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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Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns
This article has 1 author:Reviewed by ScreenIT
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Phase 1–2 Trial of a SARS-CoV-2 Recombinant Spike Protein Nanoparticle Vaccine
This article has 29 authors: -
Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis
This article has 5 authors:Reviewed by ScreenIT
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The DHODH inhibitor PTC299 arrests SARS-CoV-2 replication and suppresses induction of inflammatory cytokines
This article has 23 authors:Reviewed by ScreenIT
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The impact of social distancing and epicenter lockdown on the COVID-19 epidemic in mainland China: A data-driven SEIQR model study
This article has 4 authors:Reviewed by ScreenIT
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Efficacy and tolerability of bevacizumab in patients with severe Covid-19
This article has 25 authors:Reviewed by ScreenIT
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Clinical profile and factors associated with COVID-19 in Yaounde, Cameroon: A prospective cohort study
This article has 25 authors:Reviewed by ScreenIT
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If long-term suppression is not possible, how do we minimize mortality for COVID-19 and other emerging infectious disease outbreaks?
This article has 4 authors:Reviewed by ScreenIT
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Undetected infectives in the Covid-19 pandemic
This article has 2 authors:Reviewed by ScreenIT
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COVID-19: Mechanistic model calibration subject to active and varying non-pharmaceutical interventions
This article has 4 authors:Reviewed by ScreenIT