Factors associated with citation rates in the orthopedic literature.
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
INTRODUCTION: Investigators aim to publish their work in top journals in an effort to achieve the greatest possible impact. One measure of impact is the number of times a paper is cited after its publication in a journal. We conducted a review of the highest impact clinical orthopedic journal (Journal of Bone and Joint Surgery, American volume [J Bone Joint Surg Am]) to determine factors associated with subsequent citations within 3 years of publication. METHODS: We conducted citation counts for all original articles published in J Bone Joint Surg Am 2000 (12 issues). We used regression analysis to identify factors associated with citation counts. RESULTS: We identified 137 original articles in the J Bone Joint Surg Am. There were 749 subsequent citations within 3 years of publication of these articles. Study design was the only variable associated with subsequent citation rate. Meta-analyses, randomized trials and basic science papers received significantly more citations (mean 15.5, 9.3 and 7.6, respectively) than did observational studies (mean retrospective 5.3, prospective 4.2) and case reports (mean 1.5) (p = 0.01). These study designs were also significantly more likely to be cited in the general medical literature (p = 0.02). CONCLUSION: Our results suggest that basic science articles and clinical articles with greater methodological safeguards against bias (randomized controlled trials and meta-analyses) are cited more frequently than are clinical studies with less rigorous study designs (observational studies and case reports).
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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