Clinical pearls for the management of maxillary impacted canines: Lessons learned from 14 patients
Bibliographic record
Abstract
Despite its low prevalence, maxillary permanent canine impaction can complicate and prolong an orthodontic treatment. It also sometimes represents a root resorption risk for adjacent teeth. It is a multifactorial alteration of the dental eruption, and its causes are divided into general and local. Palatal and buccal maxillary canine impactions have different origins. Early measures can avoid their impactions in some cases. They range from deciduous canine extraction to space opening when possible. When early intervention does not provide a resolution, these cases require an interdisciplinary approach. In these situations, the orthodontist must work as a team with the periodontist or oral surgeon to uncover the impacted canine and bring it to the dental arch. This fourteen-case series will present different scenarios- ranging from early intervention to the surgical-orthodontic management of palatally and buccally impacted maxillary permanent canines.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".