The 2015 AOA North American Traveling Fellowship
Bibliographic record
Abstract
The North American Traveling Fellowship (NATF) is one of the flagship tours of the American Orthopaedic Association (AOA). NATF is geared toward advancing the careers of young orthopaedic surgeons through the promotion of clinical, scientific, and social exchange. The 2015 tour had a major emphasis on the development of leadership in the field of orthopaedics through close interactions and meetings with departmental chairs and administrators, as well as with hospital and medical school leaders. The 2015 NATF tour was in the Midwest corridor of Canada and the United States. The 5 fellows included specialists in spine, trauma, sports medicine, and shoulder and elbow surgery. Lifelong friendships and collaborations were formed during the tour. We visited 14 centers, and each site/host made great efforts to make us feel welcome and also organized excellent academic and social programs. By the conclusion of the tour, it was clear to all of us that this was a once in a lifetime experience, and we were honored to have the privilege of participating in such an amazing opportunity. The exposure to high-caliber leaders in our profession allowed us to appreciate different ways of balancing the intricacies of academic and clinical life, and these lessons will remain with us throughout our careers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.010 |
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".