Relationship between Maxillary Arch Shape and Maxillary Labial Bone Dimensions: A Pilot Study
Bibliographic record
Abstract
Abstract OBJECTIVE: To determine whether there is any relationship between the thickness of the labial alveolar bone wall in the anterior portion of the maxilla and arch shape.MATERIALS AND METHODS: Thirty patients (age, 12–53 years) were selected from archived cone beam computed tomography (CBCT) cases. All maxillary front teeth were present in all the cases. The distance between the cementoenamel junction (CEJ) and the facial bone crest and the thickness of the labial alveolar bone wall at distances of 1, 3, and 5 mm apical to the facial bone crest were measured.RESULTS: The distance between the CEJ and the facial bone crest ranged from 2.24 mm and 3.08 mm. No significant differences were found between the thickness of the bone wall at 1, 3, and 5 mm apical to the crest. A significant difference was found between the U-shaped arch on one side and the V-shaped and square-shaped arches on the other side. The U-shaped arch and labial bone wall thickness were correlated at the 1-mm distance (F = (8, 276) = 3.24, p = 0.002). U-shaped and V-shaped arches were common in women, whereas square-shaped arches were common in men (χ2 = 105.5, p = 0.000).CONCLUSION: Our study is the first to associate arch shape and labial alveolar bone wall thickness.CLINICAL RELEVANCE: The association between the U-shaped arch and bone wall thickness may constitute a new indicator for the tendency of the labial alveolar bone to resorb after extraction and placement of endo-osseous implants.
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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 | 0.001 | 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) | 0.004 | 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".