3D Analysis of maxillary incisor root inclinations in cases of unilateral maxillary canine impaction
Bibliographic record
Abstract
OBJECTIVES: To evaluate the association between maxillary incisor root inclinations and unilateral canine impaction. METHODS: A retrospective cross-sectional study of 59 pre-treatment CBCT scans (23 palatal impactions, 10 buccal impactions, and 26 comparison patients). Using Dolphin 3-D Imaging software (Chatsworth, CA), relative incisor angulations to a 3D palatal plane and the shortest distance between the canine crown and the root of the closest lateral incisor were calculated. A one-way analysis of variance was used to determine whether there were any differences between the three independent groups of impactions concerning the four continuous dependent variables incisor root inclination for each maxillary incisor. RESULTS: Patients with unilaterally impacted maxillary canines demonstrate significant differences in the root inclination position on the ipsilateral (0.0001 > P = 0.002) but not contralateral side. While palatal impactions (PIC) are associated with buccally positioned roots of the ipsilateral lateral (-9.05 degrees) and central incisors (-7.91 degrees), buccal impactions (BIC) are only associated with palatally positioned roots of the ipsilateral lateral incisors (+10.40 degrees) alone. A more labial position of the lateral incisor root was correlated with a more proximally located, coronally positioned, and medially displaced adjacent PIC (0.013 > P < 0.026). LIMITATIONS: This is a retrospective cross-sectional convenience sample. CONCLUSIONS: Patients with impacted maxillary canines, whether PIC or BIC, do not show generalized retroclination or proclination of all four maxillary incisor roots. Instead, changes in incisor root inclination were only ipsilateral to the impacted canine. BIC is only associated with palatal displacement of the ipsilateral lateral incisor root, whereas PIC is associated with labial root displacement of both ipsilateral incisors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".