Morphological Characterization of the Anterior Palatine Region Using Cone Beam Computed Tomography
Bibliographic record
Abstract
BACKGROUND: Surgery of the anterior maxillary zone has a strong impact upon dental and facial aesthetics and function. PURPOSE: To determine the anatomical characteristics and dimensions of the nasopalatine canal and alveolar bone using cone beam computed tomography (CBCT). MATERIALS AND METHODS: A retrospective, cross-sectional study was made of the nasopalatine canal in 122 randomly selected CBCT scans corresponding to 66 males (44.3%) and 56 females (55.6%). The following measurements were made: maximum length and diameters of the nasal and oral openings of the nasopalatine canal; distance from the crestal margin to the buccal wall (at apical, middle, and coronal level); and angulation of the nasopalatine canal. The anatomical variants were morphologically classified as follows: A (single canal), B (double canal), or C (Y-shaped canal). RESULTS: The anatomy of the nasopalatine canal showed important variability in terms of morphology and dimensions. Type A was observed in 48 patients (39.34%), type B in 10 (8.19%), and type C in 64 (52.45%). The mean diameter of the nasal opening or orifice was 3.02 ± 1.0 mm versus 3.29 ± 1.0 mm in the case of the oral opening. The mean length of the canal was 11.02 ± 2.4 mm. Significant differences were found between males and females, with greater canal dimensions and alveolar bone thickness values anterior to the nasal canal zone among males (p < .05). CONCLUSIONS: Our study shows gender to exert a significant influence upon the anatomical dimensions of the anterior maxilla and incisor canal. Given the anatomical variability characterizing the nasopalatine canal, we recommend CBCT evaluation prior to any type of surgery of the anterior maxillary zone.
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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 | 0.002 |
| 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) | 0.002 | 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".