Abstract: The Canadian Contribution to the Global Plastic Surgery Literature: A 10-Year Bibliometric Analysis
Bibliographic record
Abstract
INTRODUCTION: Research is an integral part of plastic surgery residency training and practice, and provides a foundation for knowledge advancement in our field. Furthermore, it improves patient care by facilitating the delivery of evidence-based therapies. As research is dynamic, and is often contingent on funding sources, it is important to continuously assess output. To our knowledge, this is the first study to describe Canadian plastic surgery research trends. MATERIALS AND METHODS: Data was obtained from the Scopus Database and articles published in the top general and specialty plastic surgery journals were included. All articles written in English and related to document-types ‘articles’, ‘reviews’, and ‘letters’ published over a 10-year period (2006–2015) were tracked. Articles were then individually analyzed, and only those who had a first and/or corresponding author with an appointment at a Canadian institution were included in the final analysis. RESULTS: Between 2006 and 2015, a total of 29,950 original articles were identified, with Canada being the 10th highest contributing country. A total of 753 Canadian articles, reviews, and letters met our inclusion criteria and were included in the final analysis. Publications followed a bimodal distribution, peaking in 2008 (n=82) and again in 2013 (n=101). There was an average of 3.53 (SD = 1.95) authors per publication. There was a 2.58:1 predominance of male to female first authors and a 5.62:1 predominance of male to female corresponding authors. The journals most frequently published in were Plastic and Reconstructive Surgery (35%), Canadian Journal of Plastic Surgery (23%), and Journal of Plastic, Reconstructive and Aesthetic Surgery (11%). The top producing institutions were the University of Toronto/University Heath Network, Dalhousie University, and McMaster University, respectively. The most frequently studied domains of plastic surgery were craniofacial (20%), hand and upper extremity (18%), and breast (12%). CONCLUSION: Canada continues to be a leading contributor of high impact research in plastic and reconstructive surgery. This study provides novel insight into a number of pertinent trends, which may be used to determine funding patterns, understudied domains of plastic surgery, domains most likely to be funded, and changes in publication practices. DISCLOSURE/FINANCIAL SUPPORT:This study was not funded. None of the authors have a financial interest to disclose.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.209 | 0.276 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".