Nasal septum deviation after rapid maxillary expansion in the early mixed dentition
Bibliographic record
Abstract
OBJECTIVES: To evaluate nasal septum changes after rapid maxillary expansion (RME) during the mixed dentition and to verify the association between quantitative and qualitative assessments of nasal septum deviation (NSD) by ear, nose, and throat (ENT) specialists. MATERIALS AND METHODS: The sample comprised 24 patients (11 male, 13 female) with a mean age of 7.62 ± 0.92 years with maxillary transverse deficiencies. Cone-beam computed tomography (CBCT) images were obtained before and after RME. Three CBCT coronal sections passing through the maxillary first molars, 5 mm anterior and 5 mm posterior, were used for quantitative assessment. NSD was calculated using the ratio of nasal cavity height to nasal septum contour. Additionally, five ENT professionals evaluated NSD qualitatively using scores from 1 to 3 through CBCT sequential axial and coronal sections. Absent NSD was scored as zero. Interstage changes were assessed using Wilcoxon tests. Spearman correlation and linear regression were performed to evaluate the association between quantitative and qualitative analyses (P < .05). RESULTS: No significant change was observed in the NSD ratio. In pre-expansion CBCT images, absence of NSD and scores 1, 2, and 3 for NSD were found for 45.8%, 41.7%, 12.5%, and 0%, respectively. In the qualitative assessment, no significant change in NSD was observed after expansion. A strong association was found between NSD ratio and ENT score (r = 0.750). CONCLUSIONS: In the mixed dentition, no significant change was observed in the NSD ratio. Qualitative analysis of NSD was associated with quantitative assessment of the ratio between nasal septum contour and nasal cavity height.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".