Biomechanical analysis of total arch maxillary distalization using infrazygomatic crest miniscrews: a finite element analysis study
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Bibliographic record
Abstract
AIM: To evaluate the maxillary incisors and canine's immediate movement tendency using three different power arms (PA) height levels during total arch maxillary distalization supported on infrazygomatic crest (IZC) miniscrews according to finite element analysis (FEA). METHODS: Three finite element models of the maxilla were developed based on CBCT imaging of a teenage male patient presenting a Class II Division 1 malocclusion in the early permanent dentition. Maxillary complex, periodontium, orthodontic accessories, IZC miniscrews and an orthodontic wire were digitally created. The PAs were placed between canines and lateral incisors and projected at 4, 7, and 10 mm height distances. After that, distalization forces were simulated between PA and IZC miniscrews. RESULTS: The anterior teeth deformation produced in the FEA models was assessed according to a Von Mises equivalent. The stress was measured, revealing tendencies of initial maxillary teeth movement. No differences were found between the right and left sides. However, there was a significant difference among models in the under-stress areas, especially the apical and cervical root areas of the maxillary anterior teeth. More significant extrusion and lingual tipping of incisors were observed with the 4 mm power arm compared to the 7 mm and 10 mm ones. The 10 mm power arm did not show any tendency for extrusion of maxillary central incisors but a tendency for buccal tipping and intrusion of lateral incisors. CONCLUSION: The maxillary incisors and canines have different immediate movement tendencies according to the height of the anterior point of the en-masse distalization force application. Based on the PA height increase, a change from lingual to buccal tipping and less extrusion tendency was observed for the incisors, while the lingual tipping and extrusion trend for canines increased.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| 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) | 0.000 | 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 it