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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Infection Density and Epidemic Size of COVID-19 in China outside the Hubei province
This article has 6 authors:Reviewed by ScreenIT
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Divergent and self-reactive immune responses in the CNS of COVID-19 patients with neurological symptoms
This article has 46 authors:Reviewed by ScreenIT
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Estimation of Coronavirus Disease 2019 (COVID-19) Burden and Potential for International Dissemination of Infection From Iran
This article has 6 authors:Reviewed by ScreenIT
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Despite vaccination, China needs non-pharmaceutical interventions to prevent widespread outbreaks of COVID-19 in 2021
This article has 18 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Identifying COVID-19 cases in outpatient settings
This article has 18 authors:Reviewed by ScreenIT
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COVIDPEN: A Novel COVID-19 Detection Model using Chest X-Rays and CT Scans
This article has 6 authors:Reviewed by ScreenIT
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LOX-1 + immature neutrophils predict severe COVID-19 patients at risk of thrombotic complications
This article has 17 authors:Reviewed by ScreenIT
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Phylodynamics reveals the role of human travel and contact tracing in controlling the first wave of COVID-19 in four island nations
This article has 14 authors:Reviewed by ScreenIT
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Transmission of aerosols through pristine and reprocessed N95 respirators
This article has 7 authors:Reviewed by ScreenIT
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Native-like SARS-CoV-2 Spike Glycoprotein Expressed by ChAdOx1 nCoV-19/AZD1222 Vaccine
This article has 23 authors:Reviewed by ScreenIT