Orthopaedic Surgery Core Curriculum: Foot and Ankle Reconstruction
Bibliographic record
Abstract
Background The purpose of this study was to develop a core curriculum for orthopaedic surgery and to conduct a national survey to assess the importance of 281 curriculum items. Attention was focused on 45 items pertaining to the foot and ankle. Methods A 281-item curriculum was developed. A content review and cross-sectional survey of a random selection of orthopaedic surgeons with primary nonacademic affiliations was completed. Data were analyzed descriptively and quantitatively using histograms, modified Hotelling's T 2 -statistic, and the Benjamini-Hochberg procedure. Our analyses assumed that each respondent answered questions independently of the answers of any other respondent but that the answers to different questions by the same respondent might be dependent. Results Of the 156 orthopaedic surgeons contacted, 131 (86%) participated in this study. Eighty-two percent (37 of 45) of the items were ranked by respondents with an average mean score higher than 3.5/4.0 and 42 higher than 3.0/40, thus suggesting that 93% of the items are important or probably important to know by the end of residency ( p = 0.07). Conclusion This study demonstrated agreement on the importance of 93% of the items that pertain to foot and ankle reconstruction to be included in a core curriculum for orthopaedic surgery. The ability to make diagnoses and to manage common fractures, soft-tissue conditions, and arthritic conditions of the foot and ankle are very important for residents to know upon graduation from their residency programs. The exceptions to these are the ability to perform primary and revision arthroplasty of the ankle.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".