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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Presence and infectivity of SARS-CoV-2 virus in wastewaters and rivers
This article has 16 authors:Reviewed by ScreenIT
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Low Baseline Pulmonary Levels of Cytotoxic Lymphocytes as a Predisposing Risk Factor for Severe COVID-19
This article has 1 author:Reviewed by ScreenIT
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TEG Max Clot Strength is Consistently Elevated and May Be Predictive of COVID-19 Status at the Time of ICU Admission
This article has 4 authors:Reviewed by ScreenIT
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Risk factors of the severity of COVID‐19: A meta‐analysis
This article has 2 authors:Reviewed by ScreenIT
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Social Media Platforms for Health Communication and Research in the Face of COVID-19 Pandemic: A Cross Sectional Survey in Uganda
This article has 2 authors:Reviewed by ScreenIT
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Circulating endothelial progenitors are increased in COVID‐19 patients and correlate with SARS‐CoV‐2 RNA in severe cases
This article has 12 authors:Reviewed by ScreenIT
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Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019
This article has 4 authors:Reviewed by ScreenIT
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Clinical, regional, and genetic characteristics of Covid-19 patients from UK Biobank
This article has 4 authors:Reviewed by ScreenIT
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Translation-Associated Mutational U-Pressure in the First ORF of SARS-CoV-2 and Other Coronaviruses
This article has 6 authors:Reviewed by ScreenIT
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Selectomic and Evolvability Analyses of the Highly Pathogenic Betacoronaviruses SARS-CoV-2, SARS-CoV, and MERS-CoV
This article has 3 authors:Reviewed by ScreenIT