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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Questionnaire assessment helps the self-management of patients with inflammatory bowel disease during the outbreak of Coronavirus Disease 2019
This article has 7 authors:Reviewed by ScreenIT
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Haplotype networks of SARS-CoV-2 infections in the Diamond Princess cruise ship outbreak
This article has 17 authors:Reviewed by ScreenIT
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A comparison study of SARS‐CoV‐2 IgG antibody between male and female COVID‐19 patients: A possible reason underlying different outcome between sex
This article has 10 authors:Reviewed by ScreenIT
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Analysis of adaptive immune cell populations and phenotypes in the patients infected by SARS-CoV-2
This article has 13 authors:Reviewed by ScreenIT
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Critical care for severe coronavirus disease 2019: a population-based study from a province with low case-fatality rate in China
This article has 12 authors:Reviewed by ScreenIT
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Factors associated with prolonged viral shedding and impact of lopinavir/ritonavir treatment in hospitalised non-critically ill patients with SARS-CoV-2 infection
This article has 7 authors:Reviewed by ScreenIT
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Elevated serum IgM levels indicate poor outcome in patients with coronavirus disease 2019 pneumonia: A retrospective case-control study
This article has 9 authors:Reviewed by ScreenIT
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Simulation-based Estimation of the Spread of COVID-19 in Iran
This article has 2 authors:Reviewed by ScreenIT
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A Review of Dosages of Chloroquine and Hydroxychloroquine for COVID-19 in registered Clinical Trials during First Quarter of 2020
This article has 2 authors:Reviewed by ScreenIT
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Core Outcome Set for Clinical Trials of COVID-19 Based on Traditional Chinese and Western Medicine
This article has 17 authors:Reviewed by ScreenIT