Predictors of Root Resorption in Lateral Incisors Adjacent to Maxillary Impacted Canines in CBCT Images: A Retrospective Study
Bibliographic record
Abstract
ABSTRACT Objectives This study aimed to assess the predictive factors of root resorption in lateral incisors adjacent to impacted maxillary canines using cone‐beam computed tomography. Material and Methods In this retrospective descriptive‐analytic study, 150 samples of impacted canines from 138 CBCT images were collected from the files of 12–35‐year‐old patients. The association between the severity and location of root resorption in lateral incisors adjacent to impacted maxillary canines and the patients’ age, sex, impacted canine's angulation, position, and follicle size was evaluated. Position and angulation of the impacted teeth were measured using the OnDemand3D software. Kruskal–Wallis test, Fisher's exact test, Mann–Whitney test, Kolmogorov–Smirnov test, Spearman's rank correlation coefficient, and multinomial logistic regression were used for data analysis. Results The probability of resorption in the middle‐third of the roots of lateral incisors decreased by 20% with each millimeter of increase in the distance between the impacted canines’ cusp tip from the occlusal plane ( p = 0.009). There was a significant association between the severity of lateral incisors’ root resorption and sex; root resorption was significantly more severe in females ( p = 0.029). Conclusions Among the evaluated variables, the vertical position of the impacted canine influenced the location of the lateral incisors’ root resorption. The severity of root resorption was higher in females.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".