Bibliographic record
Abstract
JBJS was founded by the American Orthopaedic Association in 1903 and is the Official Journal of the American Orthopaedic Association. EXCELLENCE THROUGH PEER REVIEW The Journal of Bone & Joint Surgery (JBJS) has been the most valued source of information for orthopaedic surgeons and researchers for over 125 years and is the gold standard in peer-reviewed scientific information in the field. A core journal and essential reading for general as well as specialist orthopaedic surgeons worldwide, JBJS publishes evidence-based research to enhance the quality of care for orthopaedic patients. Standards of excellence and high quality are maintained in everything we do, from the science of the content published to the customer service we provide. JBJS is an independent, non-profit journal. JBJS.org is the version of record of The Journal of Bone & Joint Surgery. JBJS is published twice a month on the first and third Wednesday of each month, each time adding to a comprehensive PDF archive dating back to 1889. Additional features online include: article commenting, social sharing links, instructional videos, podcasts, and continuing medical education activities. Contributions from anywhere in the world are welcome and considered on their merits. The manuscript must be written in English and should be submitted as outlined in the Instructions for Authors. Manuscripts are subject to blinded peer review by experts and a final decision by the editor. Papers are judged by the quality and relevance of the work. Our aim is to publish the best material available from anywhere in the world.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".