Effect of applied moment on resistance to sliding among esthetic self-ligating brackets
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of mode of ligation and bracket material on resistance to sliding (RS) by comparing various esthetic brackets of conventionally ligated and self-ligating (SL) designs under an increasing applied moment in the second-order dimension. MATERIALS AND METHODS: Eight different commercially available esthetic brackets of SL and conventional elastomeric-ligated (CL) designs were mounted on a testing apparatus to simulate canine retraction using sliding mechanics and the application of a moment on 0.019″×0.025″ stainless steel archwire. The samples examined were the CL brackets Clarity™, Inspire Ice™, SpiritMB™, and Mystique™, and the SL brackets ClaritySL™, In-OvationC™, In-OvationR™, and Smartclip™. The RS at calculated moments of 2000 g-mm and 4000 g-mm was determined and compared between the various brackets. Descriptive measures and one-way analysis of variance were used to calculate means and statistical differences among the bracket types. RESULTS: The CL monocrystalline bracket displayed significantly greater (P < .05) RS than all other brackets tested. Among the other brackets, the range of RS values was 145.8-191.7 g and 291.9-389.2 g at moments of 2000 g-mm and 4000 g-mm, respectfully, though these differences were not significant (P < .05). All brackets tested displayed greater levels of RS (P < .05) at 4000 g-mm than at 2000 g-mm. CONCLUSION: With the exception of the CL monocrystalline bracket, all brackets displayed comparable amounts of RS regardless of mode of ligation or bracket slot material.
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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 | 0.001 | 0.003 |
| 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".