ScreenIT
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 genetic element in the SARS-CoV-2 genome is shared with multiple insect species
This article has 3 authors:Reviewed by ScreenIT
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Aligning SARS-CoV-2 indicators via an epidemic model: application to hospital admissions and RNA detection in sewage sludge
This article has 6 authors:Reviewed by ScreenIT
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Incubation Period and Reproduction Number for Novel Coronavirus 2019 (COVID-19) Infections in India
This article has 7 authors:Reviewed by ScreenIT
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Monocyte CD169 Expression as a Biomarker in the Early Diagnosis of Coronavirus Disease 2019
This article has 20 authors:Reviewed by ScreenIT
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Chest CT Images for COVID-19: Radiologists and Computer-Based Detection
This article has 9 authors:Reviewed by ScreenIT
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Extracorporeal cytokine hemadsorption in severe COVID-19 respiratory failure
This article has 7 authors:Reviewed by ScreenIT
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Presence of Live SARS-CoV-2 Virus in Feces of Coronavirus Disease 2019 (COVID-19) Patients: A Rapid Review
This article has 2 authors:Reviewed by ScreenIT
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Higher pharyngeal epithelial gene expression of angiotensin-converting Enzyme-2 in patients with upper respiratory infection
This article has 6 authors:Reviewed by ScreenIT
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Outcomes and Cardiovascular Comorbidities in a Predominantly African-American Population with COVID-19
This article has 33 authors:Reviewed by ScreenIT
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Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study
This article has 2 authors:Reviewed by ScreenIT