Bibliometric study on clinical research of osteoporosis in adolescents
Bibliographic record
Abstract
Objective: Focusing on the theme of "osteoporosis-related research in adolescents," a systematic visualization of the developmental lineage, current research status, hot spots, and trends of adolescent osteoporosis was conducted to provide a reference for subsequent related research, clinical diagnosis, and treatment. Method: The Web of Science core database was used as the data source to retrieve the relevant literature and the bibliometrics method. An online bibliometric platform, CiteSpace, and VOSviewer software were used to conduct co-occurrence analysis on the authors, scientific research institutions, national cooperation, keywords, and funding sources to draw the relevant knowledge map. Result: A total of 1,199 publications from the Web of Science core database were included in this study. The number of published adolescent osteoporosis (AOP) studies has shown an upward trend over the past 29 years, with the United States being the major contributor to the field with the highest number of publications (291, 24.3%) and the highest number of citations (12,186). The international collaboration map shows that the United States is the country most focused on international collaborative exchanges, with the closest collaboration between the United States and Canada. The most influential research institutions and authors are Children's Hospital and Rauch F. the United States is the primary funding source for this research area. Research hotspots were mainly focused on "bone density," "osteoporosis," and "children." Conclusion: These knowledge maps review the research hotpots in adolescent osteoporosis research over time, analyze and summarize the research process over the past 29 years, and predict future research directions.
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How this classification was reachedexpand
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 | 0.010 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.142 | 0.227 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".