Tooth-Bone-Borne vs Bone-Borne Rapid Maxillary Expanders on Dentoskeletal Changes
Bibliographic record
Abstract
Purpose: This study compared the insertion and thickness of the cortical bone, the parallelism of the midpalatal suture, and the skeletal transverse dimension using a microimplant-assisted rapid palatal expansion (MARPE) with those produced by bone-anchored maxillary expander (BAME) in adults. Patients and Methods: The sample comprised 18 patients (mean age, 29.9±9.4 years) selected for the MARPE group and 18 (mean age 24.8±6.8 years) selected for the BAME group. Cone-Beam computed tomography scans taken just before and after the expansion. Results: After treatment, there was a significant palatal depth decrease. In addition, maxillary and mandibular width were increased in both groups. Regarding the cortical bone insertion and cortical bone width, it is shown an increase in both groups but those changes are not significant. However, the anterior suture opening effect occurs more frequently in the BAME than in the MARPE device. There are no differences in the frequency of opening of the midpalatal suture in the cases treated with MARPE and BAME, in both cases the most frequent opening morphology is parallel, independently of midpalatal suture maturation. Conclusion: There are no differences in the use of MARPE or BAME in the parallelism of the middle palatal suture, the cortical bone insertion, and thickness according to the maturation stages of the midpalatal suture but significantly increases the transverse dimensions of the maxillary skeleton.
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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 | 0.001 |
| 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".