Three-Dimensional Changes of the Auditory Canal in a Three-Year Period during Adolescence Using CBCTs
Bibliographic record
Abstract
PURPOSE: There is a lack of identifying suitable regions in the head that can be used for three-dimensional superimposition techniques. For this reason, with the use of cone-beam computed tomography (CBCT), the ear canals were analyzed to verify changes during a period of three years in the adolescent years. METHODS: CBCTs from fifty-six patients (ages: 10 to 20) were used to landmark the anatomy of the ear canals. Each patient was analyzed using two CBCT reconstructions that were taken approximately three years apart. AVIZO® software was used to locate 28 landmarks distributed following the ear canal path and foramina (ovale, spinosum, rotundum, etc.) in the cranial base to obtain spatial relationships. Three-dimensional coordinates were obtained from the landmarks, and the average distance between various landmark pairings was calculated. The repeated measure ANCOVA was used to determine statistical significance. RESULTS: In the main data set, the largest mean distance change was found to be 4.37 mm ± 18.29 mm between the left foramen ovale and the left superior medial ear canal opening. The smallest mean distance change was 0.18 mm ± 3.25 mm between the right inferior lateral ear canal opening and the right inferior medial ear canal opening. CONCLUSIONS: During the adolescent years, the ear canal presents dimensional changes. Even though in different areas throughout the canal, the average distances were minor, still, large standard deviations were present; thus, caution should be taken when trying to use this structure for superimposition of CBCTs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".