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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Epidemic analysis of COVID-19 in China by dynamical modeling
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 RNAemia Predicts Clinical Deterioration and Extrapulmonary Complications from COVID-19
This article has 60 authors:Reviewed by ScreenIT
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SARS-CoV-2 desensitizes host cells to interferon through inhibition of the JAK-STAT pathway
This article has 19 authors:Reviewed by ScreenIT
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Lockdown Effects on Sars-CoV-2 Transmission – The evidence from Northern Jutland
This article has 2 authors:Reviewed by ScreenIT
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Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States
This article has 4 authors:Reviewed by ScreenIT
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Molecular Mechanisms of Cardiac Injury Associated With Myocardial SARS-CoV-2 Infection
This article has 3 authors:Reviewed by ScreenIT
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Quantifying SARS‐CoV‐2 Infection Risk Within the Google/Apple Exposure Notification Framework to Inform Quarantine Recommendations
This article has 13 authors:Reviewed by ScreenIT
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The early dynamics of the SARS-CoV-2 epidemic in Portugal
This article has 12 authors:Reviewed by ScreenIT
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Stepping out of lockdown should start with school re-openings while maintaining distancing measures. Insights from mixing matrices and mathematical models.
This article has 5 authors:Reviewed by ScreenIT
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ELIPSE-COL: A novel ELISA test based on rational envisioned synthetic peptides for detection of SARS-CoV-2 infection in Colombia
This article has 9 authors:Reviewed by ScreenIT