Alveolar Bone Dimensions in Orthodontic Unilateral Impacted Canine Cases using Cone Beam Computed Tomography
Bibliographic record
Abstract
Impacted canines are due to missing laterals, crowding, or genetics. The alveolar bone that acts as a shock absorber distributes the masticatory forces to the underlying tissues. Objectives: To study the mean alveolar bone dimensions on the impaction and non-impaction side of Orthodontic unilateral impacted canine cases using CBCT. Methods: This descriptive cross-sectional research was organized at the Department of Orthodontics, CMH Lahore Medical College, where 165 patients were enrolled as per the selection criteria. Bucco-palatal width of the alveolar bone was measured at the level of the alveolar crest, while alveolar bone height was calculated from the alveolar crest to the nasal floor, on the impacted side. These were compared with corresponding alveolar bone dimensions on the non-impaction side, and the values were recorded. An independent samples t-test was used to find out whether any significant difference was present, and post-stratification. A p-value<0.05 was considered significant. Results: The mean age of the patients was 34.99 ± 14.69 years. There were 77 (46.7%) male and 88 (53.3%) female. On the impacted side, the mean width of alveolar bone was 6.58 ± 0.67 mm, and the mean height was 17.28 ± 0.67 mm. On the non-impacted side, the mean width and height of alveolar bone were 8.40 ± 0.96 mm and 19.01 ± 0.96 mm, respectively (p=0.001). Conclusions: The mean width and height of the alveolar bone on the impacted canine side were lower than the respective alveolar bone dimensions on the non-impacted side.
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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 | 0.001 |
| 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 | 0.000 | 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".