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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Clinical Characteristics of SARS-CoV-2 Pneumonia Compared to Controls in Chinese Han Population
This article has 9 authors:Reviewed by ScreenIT
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Clinical Characteristics of Coronavirus Disease 2019 (COVID-19): An Updated Systematic Review
This article has 7 authors:Reviewed by ScreenIT
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Mortality of COVID-19 is Associated with Cellular Immune Function Compared to Immune Function in Chinese Han Population
This article has 6 authors:Reviewed by ScreenIT
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A retrospective study of the clinical characteristics of COVID-19 infection in 26 children
This article has 7 authors:Reviewed by ScreenIT
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The epidemiological characteristics of 2019 novel coronavirus diseases (COVID-19) in Jingmen, Hubei, China
This article has 6 authors:Reviewed by ScreenIT
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Clinical Characteristics on 25 Discharged Patients with COVID-19 Virus Returning
This article has 6 authors:Reviewed by ScreenIT
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Rapid Detection of 2019 Novel Coronavirus SARS-CoV-2 Using a CRISPR-based DETECTR Lateral Flow Assay
This article has 18 authors:Reviewed by ScreenIT
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Clinical outcomes of 402 patients with COVID‐2019 from a single center in Wuhan, China
This article has 8 authors:Reviewed by ScreenIT
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Clinical Characteristics of Two Human to Human Transmitted Coronaviruses: Corona Virus Disease 2019 versus Middle East Respiratory Syndrome Coronavirus
This article has 3 authors:Reviewed by ScreenIT
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In silico approach toward the identification of unique peptides from viral protein infection: Application to COVID-19
This article has 5 authors:Reviewed by ScreenIT