Influence of skull biometrics on cosmetic reconstruction after incisivectomy and nasal planectomy reconstruction in dogs
Bibliographic record
Abstract
OBJECTIVE: To identify biometric skull measurements that are associated with tension and excess narrowing of the resultant nasal aperture during cosmetic nasal planectomy reconstruction. STUDY DESIGN: Ex vivo study. ANIMALS: Twenty cadavers of mesocephalic dogs. METHODS: Cosmetic reconstruction was performed after incisivectomy and nasal planectomy. Preoperative and intraoperative skull measurements included width of the nasal planum, rostral and caudal maxilla, labial flap, and maxilla at ostectomy site; the length of the nose, labial flap, and philtrum incision; lip thickness; and philtrum placement. Ratios of select width to length measurements were calculated. Correlation was tested between skull biometrics and tension during reconstruction as well as resulting opening of the nasal aperture. RESULTS: Breeds included golden retriever, pit bull, Labrador retriever, beagle, shepherd, basset hound, boxer mix, cocker spaniel, and Great Dane. No biometric ratios were predictive of procedural success. The most important objective measurements that were significantly correlated with inferior outcome included width of the nasal planum (>3 cm), width of the caudal maxilla (>6.2 cm), lip thickness (>0.5 cm), width of the labial flap (>2.9 cm), length of the incision created to make the cosmetic "philtrum" (longer incisions >2.8 cm), and philtrum placement (more dorsal placement). CONCLUSION: Tension during reconstruction and decreased resultant nasal aperture were associated with wider facial features and thicker lips as well as directly impacted by cosmetic philtrum design and placement. CLINICAL SIGNIFICANCE: Standardized preoperative measurements may help guide clinical decision making in choosing and executing a nasal planectomy reconstructive technique.
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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 | 0.001 |
| 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 | 0.000 | 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".