The international rank order of publications in major clinical orthopaedic journals from 2000 to 2004
Bibliographic record
Abstract
Publications in peer-reviewed journals are the most important determinant by which research is rated and funding awarded.In this study, the publication rate in orthopaedic surgery of individual countries was scored in selected clinical journals in order to identify those which are making the principal contributions to the development of the orthopaedic discipline.A total of 15 major clinical orthopaedic journals was selected.All articles with abstracts were scored for the country of the corresponding author through a bibliometric search in Medline/PubMed over a period of five years (2000 to 2004).The total number of publications, the number adjusted for size of population and the impact factor of the journal were assessed for each country.A total of 13 311 articles were scored, of which 92% were generated by 15 countries with 47.4% by the United States, followed by Japan (8.0%) and the United Kingdom (7.3%).Corrected for population size, eight smaller European countries led this ranking with Sweden, Switzerland and Finland at the top, with the United States in their midst in sixth place.Japan and Finland scored the highest mean impact factor.This observational study demonstrates that the United States is the most productive country in absolute number of publications in the selected clinical orthopaedic journals, and when normalised for population size, the smaller European countries with a high proficiency in English were most successful.Our objective was to identify the countries which generate knowledge and progress in orthopaedic surgery and consider the factors that enabled them to be major contributors.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.041 | 0.045 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.021 |
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".