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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The SARS-CoV-2 Cytopathic Effect Is Blocked by Lysosome Alkalizing Small Molecules
This article has 26 authors:Reviewed by ScreenIT
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Electrophysiological and Proarrhythmic Effects of Hydroxychloroquine Challenge in Guinea-Pig Hearts
This article has 20 authors:Reviewed by ScreenIT
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Developing a Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein Model in a Viral Membrane
This article has 12 authors:Reviewed by ScreenIT
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A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys
This article has 25 authors:Reviewed by ScreenIT
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How many patients will need ventilators tomorrow?
This article has 4 authors:Reviewed by ScreenIT
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Trimeric SARS-CoV-2 Spike interacts with dimeric ACE2 with limited intra-Spike avidity
This article has 21 authors:Reviewed by ScreenIT
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Computational analysis of dynamic allostery and control in the SARS-CoV-2 main protease
This article has 2 authors:Reviewed by ScreenIT
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Fractional diffusion on the human proteome as an alternative to the multi-organ damage of SARS-CoV-2
This article has 1 author:Reviewed by ScreenIT
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Kidney and Lung ACE2 Expression after an ACE Inhibitor or an Ang II Receptor Blocker: Implications for COVID-19
This article has 5 authors:Reviewed by ScreenIT
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In-Vivo Toxicity Studies and In-Vitro Inactivation of SARS-CoV-2 by Povidone-iodine In-situ Gel Forming Formulations
This article has 14 authors:Reviewed by ScreenIT