Yoga's Evolution in Sports Science:A Bibliometric Assessment of Research Trends
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This bibliometric assessment delves into the evolving relationship between yoga and sports science, exploring the interdisciplinary convergence of ancient holistic practices and modern athletic performance optimization. With a systematic approach employing the Web of Science database, this study analyzes 111 scholarly documents published between 2013 and 2023, providing insights into thematic trends, prolific authors, influential journals, and global contributions. The research showcases a steady annual growth rate of 4.14%, indicating a sustained interest in the subject. Collaborative efforts are evident, with an average of 4.47 co-authors per document and 18.92% international collaborations. The United States emerges as a research leader with 41 articles, closely followed by Australia, Canada, and China. These contributions highlight the multifaceted benefits of yoga in enhancing athletic prowess, injury prevention, and overall well-being. As global interest intensifies, this analysis underscores the importance of interdisciplinary cooperation and cross-cultural exploration to harness yoga's potential within sports science for informed practices and future advancements. Keywords: Yoga, Sports Science, Bibliometric Analysis.
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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: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.115 | 0.229 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it