Presurgical Unilateral Cleft Lip Anthropometrics and the Presence of Dental Anomalies
Bibliographic record
Abstract
OBJECTIVE: To investigate associations between cleft lip anthropometrics and dental anomalies in the permanent dentition in unilateral cleft lip patients. DESIGN: Retrospective cross-sectional study. PATIENTS: Children with unilateral clefts of the lip, with or without cleft palate. METHODS: Anthropometric lip measurements, made immediately prior to lip repair, were available for each patient. The presence of dental anomalies in the permanent dentition was assessed radiographically. The presence of associations between anthropometric lip measurements and prevalence rates of different dental anomalies were determined using logistic regression analyses. RESULTS: In the 122 included patients, the cleft lateral lip element was deficient in height in 80% and in transverse length in 84% of patients. Patients with more deficient cleft side lateral lip height and less deficient cleft side lateral lip transverse length were more likely to present with cleft side maxillary lateral incisor agenesis. On the other hand, patients with a less deficient cleft side lateral lip height and more deficient cleft side lateral lip transverse length were more likely to present with a cleft side supernumerary maxillary lateral incisor. When looking only at incomplete clefts, the cleft side lateral lip transverse length deficiency was more predictive of the presence of supernumerary maxillary lateral incisors (P = .030), while for complete clefts, the cleft side lateral lip height deficiency was more predictive of the presence of maxillary lateral incisor agenesis (P = .035). CONCLUSIONS: In patients with unilateral clefts, cleft lip anthropometrics have a predictive role in determining the occurrence of dental anomalies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".