Authorship in the field of femoroacetabular impingement: an analysis of journal publications
Bibliographic record
Abstract
PURPOSE: This review provides a bibliometric analysis of the contributors to the field of FAI research. METHODS: A comprehensive search of three databases (MEDLINE, EMBASE, and PubMed) was performed to identify all clinical research articles on the topic of FAI (from inception to 2015). Cadaveric and animal studies were excluded. Study characteristics including authors, residing country of corresponding author, and journal were abstracted from the respective databases. RESULTS: In total, 1073 articles were included in this review. There were a total of 5471 different authors who contributed to the field of FAI research, 28.3 % of whom were only published in one article. The top 20 authors were associated with over half of all publications, and research studies were typically performed in their countries of residence. The greatest proportion of FAI-related articles was published in the Journal of Arthroscopy and Clinical Orthopaedics and Related Research. CONCLUSIONS: The number of authors contributing to FAI research is increasing, suggesting not only increasing prevalence of FAI treatment among orthopaedic surgeons but also increasing interest among hip arthroscopists in furthering understanding regarding the diagnosis and management of the condition. The number of publications produced by the top 20 authors (and their affiliated countries: USA, Switzerland, Canada, and the UK) is expected to contribute to a majority of future publications. Current trends suggest that the quality of evidence will continue to improve in the near future, as large-scale, collaborative studies are currently underway. LEVEL OF EVIDENCE: Retrospective study, Level IV.
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
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 | 0.019 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.101 | 0.112 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".