Level of evidence and authorship trends of clinical studies in knee surgery, sports traumatology, arthroscopy, 1995–2015
Bibliographic record
Abstract
PURPOSE: There is increasing emphasis on publication quality and internationalization of author groups in orthopaedic literature. The purpose of this review was to evaluate the type of studies and the level of evidence (LOE) published in knee surgery, sports traumatology, arthroscopy (KSSTA) from 1995 to 2015. The secondary aim was to analyze trends in authorship characteristics in KSSTA. METHODS: Two reviewers reviewed the table of contents of KSSTA and identified original papers from 1995, 2000, 2005, 2010, and 2015. The reviewers graded LOE from Levels I to IV using guidelines from the University of Oxford's Centre for Evidence-Based Medicine. For each article, the total number of authors and country of author group were also analyzed. RESULTS: A total of 880 papers were analyzed. The proportions in LOE have stayed consistent throughout the study period (n.s.). There has been a significant increase in the number of published articles and the number of Level I and II studies (P < 0.01). Therapeutic articles were the most common type. The mean number of authors per KSSTA article significantly increased from 3.9 to 5.7 over the 20-year period (P < 0.01). The number of represented countries increased yearly and academic institutions from 40 different nationalities published articles in the Journal. Of the examined years, the percent of articles with international collaboration was 17.6%. CONCLUSION: The proportion of LOE I and II articles published in KSSTA remains consistently high. Therapeutic studies are the most frequently published articles. There is an increase in international groups publishing in KSSTA. LEVEL OF EVIDENCE: 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 | 0.039 | 0.244 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.037 | 0.039 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".