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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Kynurenic acid may underlie sex-specific immune responses to COVID-19
This article has 22 authors:Reviewed by ScreenIT
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Multicentre Performance Evaluation of the Elecsys Anti-SARS-CoV-2 Immunoassay as an Aid in Determining Previous Exposure to SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT
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Estimating COVID-19 hospital demand using a non-parametric model: a case study in Galicia (Spain)
This article has 4 authors:Reviewed by ScreenIT
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Spatial epidemiological study of the distribution, clustering, and risk factors associated with early COVID-19 mortality in Mexico
This article has 4 authors:Reviewed by ScreenIT
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Broncho-alveolar inflammation in COVID-19 patients: a correlation with clinical outcome
This article has 22 authors:Reviewed by ScreenIT
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Fluorescent Glycan Fingerprinting of SARS2 Spike Proteins
This article has 2 authors:Reviewed by ScreenIT
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Comparative analysis of the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state
This article has 1 author:Reviewed by ScreenIT
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An integrated rural health system baseline assessment of COVID-19 preparedness in Siaya Kenya
This article has 8 authors:Reviewed by ScreenIT
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Excess deaths in Spain during the first year of the COVID–19 pandemic outbreak from age/sex–adjusted death rates
This article has 1 author:Reviewed by ScreenIT
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Incidence and risk factors for persistent symptoms in adults previously hospitalized for COVID‐19
This article has 35 authors:Reviewed by ScreenIT