The in vitro biomechanics of anterior arch expansion using fixed lingual appliances with coil springs or archwire stops
Bibliographic record
Abstract
INTRODUCTION: The presented study investigates differences in the biomechanics of straight and mushroom fixed lingual appliances when implementing coil springs and stops for anterior arch expansion. MATERIALS AND METHODS: An in vitro orthodontic simulator was used to measure three-dimensional forces and moments on each tooth of a simulated maxillary arch. Mushroom and straight archwire forms of 0.016″ NiTi round archwire were considered, using 0.010″ × 0.030″ NiTi open coils and 0.016″-0.018″ archwire stops (n = 44 per group). Teeth in the anterior dental arch were moved from a neutral to crowded position to replicate anterior crowding of central and lateral incisors. Forces and moments of interest for lateral incisors and first premolars were compared using repeated measures mixed multivariate analysis of variance (α = 0.05). RESULTS: Three comparisons between straight versus mushroom archwires and two comparisons of coil springs vs. stops were not statistically significant. Overall, it was found that the use of a straight lingual archwire produced larger differences in forces and moments between using stops and coil springs than when using a mushroom archwire. Using stops produced larger forces and moments for both types of archwires as compared to using coil springs. The largest expansion forces were produced using straight archwires with stops, exceeding 3.0 N of force. Straight archwires with coil springs produced the lowest expansion forces on lateral incisors, just exceeding 1.5 N. CONCLUSIONS: The findings of this study have elucidated significant differences in the biomechanics of transverse arch expansion using straight or mushroom fixed lingual appliances with coil springs or stops.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".