Bibliographic record
Abstract
The presentation of the Kappa Delta Award papers are a highlight of the Orthopaedic Research Society meeting as they represent the very pinnacle of orthopaedic research done by young and established investigators. The 2015 Ann Doner Vaughn Award winner is Dr. Steven A. Olson and his colleagues, Bridgette Furman, Virginia Kraus, Janet Huebner, and Farshid Guilak. His award paper is presented in this issue of the Journal of Orthopaedic Research entitled “Therapeutic Opportunities to Prevent Post-Traumatic Arthritis: Lessons from the Natural History of Arthritis after Articular Fracture.” Established in 1947 by the Kappa Delta Sorority to honor outstanding accomplishments in orthopaedic research, two of the Awards are named for Presidents of the Sorority who were instrumental in bringing the awards to fruition and the third Award is the Young Investigator Award. The Awards are offered by the American Academy of Orthopaedic Surgeons via the Kappa Delta Research Fellowship in Orthopaedics and open to all members of the American Academy of Orthopaedic Surgeons, Orthopaedic Research Society, Canadian Orthopaedic Association, or the Canadian Orthopaedic Research Society. Importantly, many recipients have cited the Kappa Delta Awards as having been decisive factor in encouraging them to continue in the field of research. Award papers can be submitted to the Journal of Orthopaedic Research for publication. Please the AAOS and ORS websites for submission requirements and past winners. Congratulations to Dr. Olson and his team for an outstanding body of research, meeting presentation, and publication. Linda J. Sandell, PhD Editor in Chief, JOR
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 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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".