A Cleft-Customized Occlusal Rating System to Assess Orthodontic Occlusal Improvement in Patients With Unilateral Cleft Lip and Palate
Bibliographic record
Abstract
OBJECTIVE: This study aimed to develop a new method to quantify occlusal improvement in patients with unilateral cleft lip and palate (UCLP) who had undergone orthodontic treatment and to evaluate its reproducibility. DESIGN: A panel of orthodontists decided on the relevance of different occlusal features to score initial and final 3-dimensional study models and panoramic radiographs. A subsequent subjective analysis was later performed by a local orthodontic panel. SETTING: The sample was obtained from the orthodontic clinical archives of a hospital known for the treatment of patients with craniofacial differences. PATIENTS: Thirty-one nonsyndromic patients, 17 males and 14 females, were randomly selected according to preestablished inclusion/exclusion criteria. INTERVENTIONS: The records corresponded to the period during which the patients were treated with conventional multibracket mechanics and adjunctive restorative procedures. MAIN OUTCOME/MEASURES: The intraclass correlation coefficient measured intraexaminer and interexaminer agreements. The Spearman correlation test assessed the relationship between the local orthodontic panel perception and the improvement scores. RESULTS: Inter- and intra-rater ICCs varied between fair/good to excellent. There was a strong correlation between the Cleft-Customized Occlusal Rating system classification of occlusal improvement and the local orthodontic panel's perception, thereby enabling the utilization of the interpretation scale by the panel. CONCLUSIONS: The method showed to be a useful tool in quantifying and classifying occlusal improvement in this specific population. As any other method, some limitations apply and need to be accounted for.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".