Mandibular Incisive Canal: Cone Beam Computed Tomography
Bibliographic record
Abstract
PURPOSE: Panoramic radiography is often used to analyze the anatomical structure of the teeth, jaws, and temporomandibular joints. Cone beam computed tomography (CBCT) imaging allows multiple axial slices of the image to be obtained through these anatomical structures. The aim of this study was to assess CBCT compared with panoramic radiography to verify the presence, location, and dimensions of the mandibular incisive canal. MATERIALS AND METHODS: CBCT scan images and panoramic radiographs of 89 subjects were compared for the presence of the mandibular incisive canal, its location, size, and anterior-posterior length. The distance between the incisive canal and the buccal and lingual plate of the alveolar bone, and the distance from the canal to the inferior border of the mandible and the tooth apex were also measured. A paired t-test was used to calculate any significant difference between the two imaging techniques. RESULTS: Eighty-three percent of the CBCT scans showed the presence of the incisive canal, as did 11% of the panoramic radiographs. The range of the incisive canal diameter, as seen in the CBCT scans, was from 0.4 × 0.4 mm to 4.6 × 3.2 mm. The mean length of the canal was 7 ± 3.8 mm. The distance from the inferior border of the mandible to the canal was 10.2 ± 2.4 mm, and the mean distance to the buccal plate was 2.4 mm. The apex-canal distance (in dentate subjects) was 5.3 mm. CONCLUSION: The presence, location, and dimensions of the mandibular incisive canal are better determined by CBCT imaging than by panoramic radiography.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 0.001 |
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".