As F1000 scores and the number of citations increase for articles, the greater the percentage of articles are included in Wikipedia. 

Exploring the Use of Social Media to Measure Journal Article Impact Figure

What was found was that journal articles referenced in Wikipedia had higher citation counts and F1000 scores than a random equivalent subset. As citation counts and F1000 scores increased, the more likely it would be for the article to be included in Wikipedia. 

University of California, Berkeley

Researchers downloaded the data from Wikipedia on January 30, 2010 that contained 19 million pages. They then extracted all PubMed journal article references from this data. They then took citation information scores from Faculty of 1000 (F1000) and PubMed Central (PMC) for PubMed journal articles published before 2010. To then also compare articles referenced in Wikipedia and those that are not, they calculated the probability of getting citation counts or scores that are similar by randomly drawing articles from F1000 and PMC. They took their data from Wikipedia and compared it to journal article citation counts and F1000 scores. They used PMC to find the journal article citation counts for about 19000 articles referenced in Wikipedia, and F1000 to find scores for 5000 articles referenced in Wikipedia. 

Exploring the Use of Social Media to Measure Journal Article Impact Methodology

Evans, P., & Krauthammer, M. (2011). Exploring the use of social media to measure journal article impact. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011, 374–381. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243242/ 

Exploring the Use of Social Media to Measure Journal Article Impact

Exploring the Use of Social Media to Measure Journal Article Impact Results

Researchers also found that most articles published after 2009 were referenced on Wikipedia a few months after having been published. Articles are also being included in Wikipedia faster as time has progressed.

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