Skeletal, Dental, and Nasal Changes After Slow Maxillary Expansion Using Quad-Helix
Bibliographic record
Abstract
The objective of this study was to assess the transverse maxillary skeletal, dental, and nasal effects of quad-helix treatment (slow maxillary expansion) in comparison to an untreated group. This study was performed on 24 patients. Before and after treatment, CBCT images for children who were treated with Wilson quad-helix were retrieved. The treatment group included 12 children with a mean age of 11.4 ± 1.2 years. The untreated control group had 12 matching patients aged 11.7 ± 0.7 years. AVIZO software (version 9.1) was utilized to place specific 3D anatomical landmarks. The segmentation of the nasal airway was performed using Mimics. The maxillary inter-molar width and inter-premolar widths increased significantly in the treatment group but not in the comparison group. These increases were statistically greater between groups. This study showed statistically significant increases in maxillary inter-molar and inter-premolar widths in patients who were treated with Wilson quad-helix to expand their upper arch. Buccal translation in the upper molars resulted after treatment. Quad-helix treatment caused more dental than skeletal effects. The nasal volume and surface area in the quad-helix group significantly increased.
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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 | 0.000 |
| 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) | 0.002 | 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".