Measurement of forces and moments around the maxillary arch for treatment of a simulated lingual incisor and high canine malocclusion using straight and mushroom archwires in fixed lingual appliances
Bibliographic record
Abstract
INTRODUCTION: An Orthodontic SIMulator (OSIM) was used to investigate the propagation of forces and moments around a simulated archform for a gingival displaced canine and lingual displaced lateral incisor using fixed lingual orthodontic appliances. METHODS: In-Ovation L self-ligating lingual brackets were bonded to anatomically shaped teeth on the OSIM, and the teeth were positioned such that a G4 NiTi 0.016" large maxillary mushroom archwire could be ligated in passive position. Each trial consisted of two movements: a 3mm lingual displacement of the 1-2 lateral incisor at 0.2 mm increments, and a 1.5 mm gingival displacement of the 2-3 canine at 0.15 mm increments (n = 50). Anterior brackets were repositioned to accommodate G4 NiTi 0.016" universal straight archwires (n = 50). Tests were completed at 37°C, and force and moment data in all directions was collected for each tooth around the arch at all increments. RESULTS: In general, the straight archwire produced significantly larger forces and moments at the centre of resistance for teeth of interest than did mushroom archwires. Specifically, the straight archwire produced 2.62 N and 3.81 N more force in the direction of tooth movement on the tooth being moved for a gingival displaced canine and lingual displaced lateral incisor, respectively, as compared to mushroom archwires. CONCLUSIONS: Results from this study suggest that mushroom archwires may provide better mechanics for movement of teeth in the anterior segment when using a round archwire; however, only biomechanical data was considered in this study and there are many factors that need to be considered in treatment planning.
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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) | 0.001 | 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".