Provision and timing of interceptive orthodontic treatment by certified orthodontists and pediatric dentists in Canada.
Bibliographic record
Abstract
Introduction: The ideal timing to initiate orthodontic treatment is an important, yet controversial issue. The purpose of this study was to investigate the provision of orthodontic care for 7 types of skeletal dysplasia by paediatric dentists and orthodontists in Canada. Methods: A questionnaire was distributed to randomly selected orthodontists (N=140) and paediatric dentists (N=132) throughout Canada. Surveys returned within 8 weeks were included for c2 statistical analysis. Results: The response rate was 59% for orthodontists and 54% for pediatric dentists. Orthodontists and pediatric dentists differed significantly in the timing of their first orthodontic consultation (p < 0.01). More pediatric dentists used to the dental age to determine the appropriate time to initiate treatment (p < 0.01), whereas more orthodontists relied on the pubertal indicators (p < 0.01). More orthodontists would intervene in the early mixed dentition for moderate mandibular prognathia (p < 0.01); mid-mixed dentition for severe mandibular retrognathia (p < 0.01), late mixed dentition for moderate mandibular retrognathia (p < 0.01) and permanent dentition for skeletal openbite and severe mandibular prognathia (p < 0.01). Most pediatric dentists would intervene in the early and mid-mixed dentition for the specified cases of skeletal malocclusions (p < 0.05). Conclusions: The results of this investigation indicate both consistencies and variation between orthodontic and paediatric practitioners with regard to preference in treatment timing, and the factors that influence these decisions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".