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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X-ray Structure of Main Protease of the Novel Coronavirus SARS-CoV-2 Enables Design of α-Ketoamide Inhibitors
This article has 5 authors:Reviewed by ScreenIT
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Structural basis for the recognition of the 2019-nCoV by human ACE2
This article has 5 authors:Reviewed by ScreenIT
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Crystal structure of the 2019-nCoV spike receptor-binding domain bound with the ACE2 receptor
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 and SARS-CoV Spike-RBD Structure and Receptor Binding Comparison and Potential Implications on Neutralizing Antibody and Vaccine Development
This article has 9 authors:Reviewed by ScreenIT
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Evidence for Gastrointestinal Infection of SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Estimating the case fatality ratio of the COVID-19 epidemic in China
This article has 16 authors:Reviewed by ScreenIT
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Pangolin homology associated with 2019-nCoV
This article has 3 authors:Reviewed by ScreenIT
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Clinical and immunological features of severe and moderate coronavirus disease 2019
This article has 20 authors:Reviewed by ScreenIT
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COVID‐19 in a designated infectious diseases hospital outside Hubei Province, China
This article has 14 authors:Reviewed by ScreenIT
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Estimation of the Excess COVID-19 Cases in Seoul, South Korea by the Students Arriving from China
This article has 4 authors:Reviewed by ScreenIT