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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Substantial underestimation of SARS-CoV-2 infection in the United States
This article has 13 authors:Reviewed by ScreenIT
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Proinflammatory IgG Fc structures in patients with severe COVID-19
This article has 27 authors:Reviewed by ScreenIT
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Video Consultation During the COVID-19 Pandemic: A Single Center's Experience with Lung Transplant Recipients
This article has 6 authors:Reviewed by ScreenIT
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Evaluation of the U.S. governors' decision when to issue stay‐at‐home orders
This article has 3 authors:Reviewed by ScreenIT
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A citizen science initiative for open data and visualization of COVID-19 outbreak in Kerala, India
This article has 17 authors:Reviewed by ScreenIT
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Early experience with COVID-19 patients at academic hospital in Southwestern United States
This article has 5 authors:Reviewed by ScreenIT
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Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass Opacities
This article has 10 authors:Reviewed by ScreenIT
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Establishment of an African green monkey model for COVID-19
This article has 15 authors:Reviewed by ScreenIT
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Nrf2 Activator PB125 ® as a Potential Therapeutic Agent Against COVID-19
This article has 4 authors:Reviewed by ScreenIT
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REMBRANDT: A high-throughput barcoded sequencing approach for COVID-19 screening
This article has 5 authors:Reviewed by ScreenIT