Segmental Bone and Cartilage Reconstruction of Major Nasal Dorsal Defects
Bibliographic record
Abstract
This article describes the results of segmental bone and cartilage reconstruction of significant nasal dorsal defects. Solid bone graft reconstructions frequently lead to an unnatural hardness of the nasal tip. Rib cartilage reconstructions are pliable and soft but are a problem because they easily undergo warpage. The operation is performed using the open approach. Outer cranial bone graft is used for the bone component and extends at least two-thirds of the length of the dorsum. It is secured in place with a compression screw and a Kirschner wire. The cartilage component consists of an abbreviated L strut constructed of septal or conchal cartilage. It is slotted into the cranial bone in a tongue-in-groove manner and is sutured to it through a drill hole in the bone. The dorsal profile is completed with a single cartilage onlay graft or multiple sagittal cartilage grafts secured to the sides of the L strut. Twelve patients underwent segmental reconstruction of nasal deformities. Within this group, five patients underwent secondary rhinoplasty, five underwent posttraumatic rhinoplasty, and two underwent nose augmentation for Oriental features. There were seven men and five women. In all cases, good nasal tip mobility was maintained, and the nasal tips were soft. The interface between the bone graft and cartilage graftwas well camouflaged. The two did not separate. This procedure follows the principle of replacing lost tissue with like materials.
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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 | 0.000 |
| 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) | 0.002 | 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".