The use of autogenous costal cartilage graft in septorhinoplasty
Bibliographic record
Abstract
INTRODUCTION: Reconstructive septorhinoplasty in complex nasal deformities often requires harvesting a large amount of tissue for grafting. Autogenous septal cartilage has generally been considered the gold standard grafting material. The aim of this paper was to report our experience with the use of costal cartilage grafts in cases with significant structural deformities and insufficient septal cartilage. DESIGN: Retrospective chart review. PATIENTS: Between 1998 and 2006, 37 patients underwent septorhinoplasty using costal cartilage as the primary source for grafting. Twenty-two men and 14 women with a median age of 42 were enrolled in the study. Patient demographics, indications for surgery, and immediate and late complications were reviewed. The follow-up range was 3 to 72 months. CONCLUSIONS: Autogenous costal cartilage graft is a viable option in reconstructive septorhinoplasty. We advocate the use of this graft in septorhinoplasty cases requiring a large volume of tissue and insufficient septal cartilage.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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 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".