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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Trace, Quarantine, Test, Isolate and Treat: A Kerala Model of Covid-19 Response
This article has 4 authors:Reviewed by ScreenIT
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A New Hematological Prognostic Index For Covid-19 Severity
This article has 16 authors:Reviewed by ScreenIT
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Conservative management of acute appendicitis in the era of COVID 19: A multicenter prospective observational study at the United Arab Emirates
This article has 5 authors:Reviewed by ScreenIT
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The current state of COVID-19 in Australia: importation and spread
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 Detection on Chest X-Ray and CT Scan Images Using Multi-image Augmented Deep Learning Model
This article has 4 authors:Reviewed by ScreenIT
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Host range projection of SARS-CoV-2: South Asia perspective
This article has 4 authors:Reviewed by ScreenIT
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Estimating COVID-19 cases and outbreaks on-stream through phone calls
This article has 6 authors:Reviewed by ScreenIT
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How vaccination and contact isolation might interact to suppress transmission of Covid-19: a DCM study
This article has 4 authors:Reviewed by ScreenIT
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A Highly Specific Assay for the Detection of SARS-CoV-2–Reactive CD4+ and CD8+ T Cells in COVID-19 Patients
This article has 10 authors:Reviewed by ScreenIT
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Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks
This article has 4 authors:Reviewed by ScreenIT, Rapid Reviews Infectious Diseases