Bibliographic record
Abstract
BACKGROUND: Reconstruction of acquired auricular defects is a challenging procedure. Since its emergence, the helical advancement technique has proved to be an excellent method of repairing many auricle defects. This technique may occasionally result in an alteration in the dimensions of the neoauricle, with subsequent deformity. However, the advantages of this technique are well known, while the pitfalls are scarce. OBJECTIVE: To critically review the selection criteria of patients with acquired auricular defects to determine which are eligible for helical advancement technique without subsequent deformity. METHODS: From March 2004 to January 2006, 18 patients with three types of upper one-third auricle defects underwent the helical advancement procedure. All patients were male, with mean age of 33.5 years. The defects ranged from 1.2 cm to 4.3 cm in length. Two helical flaps (one on either side of the injury) were advanced along the helical margin to ensure closure. The vertical and horizontal auricular axes were measured before and after surgery, and the actual reduction in millimetres was calculated. Patients were followed up for three months postoperatively. Assessment of the surgical outcome was performed by surgeon (with patient feedback) in the final patient visit. RESULTS: The principle pitfall in the form of small neoauricle with or without cupping was reported in five patients (27.77%). The defects in these cases were >2.8 cm and the mean resultant reduction in vertical axes was >5 mm. Statistical analysis resulted in χ(2)=4.24 and P=0.04. CONCLUSION: The three varieties of upper one-third auricle defects can best be corrected by the helical advancement technique when the defect is <2.8 cm. Furthermore, perioperative reduction in the vertical axis of the neoauricle >5 mm was an important predictive factor in the development of subsequent deformity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".