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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Multiple-Input Deep Convolutional Neural Network Model for COVID-19 Forecasting in China
This article has 4 authors:Reviewed by ScreenIT
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History of coronary heart disease increased the mortality rate of patients with COVID-19: a nested case–control study
This article has 8 authors:Reviewed by ScreenIT
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Clinical Characteristics of Hospitalized Patients with SARS-CoV-2 and Hepatitis B Virus Co-infection
This article has 15 authors:Reviewed by ScreenIT
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Anaesthesia and infection control in cesarean section of pregnant women with coronavirus disease 2019 (COVID-19)
This article has 11 authors:Reviewed by ScreenIT
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Anaesthetic managment and clinical outcomes of parturients with COVID-19: a multicentre, retrospective, propensity score matched cohort study
This article has 10 authors:Reviewed by ScreenIT
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Clinical features and the maternal and neonatal outcomes of pregnant women with coronavirus disease 2019
This article has 13 authors:Reviewed by ScreenIT
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Disparities in Age-specific Morbidity and Mortality From SARS-CoV-2 in China and the Republic of Korea
This article has 2 authors:Reviewed by ScreenIT
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Mechanical Ventilator Milano (MVM): A Novel Mechanical Ventilator Designed for Mass Scale Production in Response to the COVID-19 Pandemics
This article has 26 authors:Reviewed by ScreenIT
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Gastrointestinal tract symptoms in coronavirus disease 2019: Analysis of clinical symptoms in adult patients
This article has 5 authors:Reviewed by ScreenIT
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Quantifying treatment effects of hydroxychloroquine and azithromycin for COVID-19: a secondary analysis of an open label non-randomized clinical trial
This article has 1 author:Reviewed by ScreenIT