Guidance for the Clinical Management of Impacted Maxillary Canines.
Bibliographic record
Abstract
In this study of orthodontic and surgical management of impacted maxillary canines, the current literature is reviewed and a decision tree is presented to assist clinicians in determining the optimal treatment based on available evidence. Impacted canines have a prevalence of 2% and are more common in females. Palatal impactions are present in around 75% of cases. These trends are observed worldwide with small variations in different populations. Diagnosis through clinical examination and conventional imaging can be complemented with cone-beam computed tomography imaging when necessary. Early intervention by extraction of deciduous canines is indicated when the canine is impacted in sectors 2 or 3 and has an angle of 20 to 30 degrees in relation to the vertical line. Other early management approaches involve rapid palatal expansion or distalization of posterior teeth, when possible. Surgical orthodontic treatment is required when early intervention is unsuccessful. For buccal impactions, the canine position relative to the mucogingival junction determines the choice of surgical procedure; for palatal impactions, the open surgical procedure seems to be preferred. In some situations, however, a closed eruption has precise indications. Use of efficient orthodontic mechanics reduces treatment complications and may be complemented with the use of nitinol piggybacks, swinging gates, modified transpalatal arches, and temporary anchorage devices. Frequent complications with impactions include canine ankylosis, root resorption of the neighboring lateral or central incisor, and gingival esthetic differences between the impacted canine and the contralateral canine upon treatment completion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".