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Abstract: The Canadian Contribution to the Global Plastic Surgery Literature: A 10-Year Bibliometric Analysis

2016· article· en· W2522666184 on OpenAlexaboutno aff
Alexander Morzycki, Jason B. Williams

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2016
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsScopusSpecialtyInclusion (mineral)MedicineFamily medicineLibrary scienceMEDLINEPsychologyPolitical scienceSocial scienceSociology

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.079
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.291
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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