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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A novel artificial intelligence-assisted triage tool to aid in the diagnosis of suspected COVID-19 pneumonia cases in fever clinics
This article has 23 authors:Reviewed by ScreenIT
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Predicting the evolution of SARS-Covid-2 in Portugal using an adapted SIR Model previously used in South Korea for the MERS outbreak
This article has 1 author:Reviewed by ScreenIT
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Dynamic profile of severe or critical COVID-19 cases
This article has 1 author:Reviewed by ScreenIT
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Clinical characteristics of COVID-19 in 104 people with SARS-CoV-2 infection on the Diamond Princess cruise ship: a retrospective analysis
This article has 15 authors:Reviewed by ScreenIT
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Favipiravir Versus Arbidol for Clinical Recovery Rate in Moderate and Severe Adult COVID-19 Patients: A Prospective, Multicenter, Open-Label, Randomized Controlled Clinical Trial
This article has 14 authors:Reviewed by ScreenIT
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Characterization of anti-viral immunity in recovered individuals infected by SARS-CoV-2
This article has 17 authors:Reviewed by ScreenIT
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Is a 14-day quarantine period optimal for effectively controlling coronavirus disease 2019 (COVID-19)?
This article has 8 authors:Reviewed by ScreenIT
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A serological assay to detect SARS-CoV-2 seroconversion in humans
This article has 30 authors:Reviewed by ScreenIT
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Temporal dynamics in viral shedding and transmissibility of COVID-19
This article has 23 authors:Reviewed by ScreenIT
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Correcting under-reported COVID-19 case numbers: estimating the true scale of the pandemic
This article has 4 authors:Reviewed by ScreenIT