The effect of buccal–lingual slot dimension size on third-order torque response
Bibliographic record
Abstract
Introduction: The focus of the presented study was to investigate the effect of buccal-lingual (B-L) orthodontic bracket slot dimension on third-order torque mechanics. Materials and methods: Three types of orthodontic brackets and two archwire sizes were considered. Ortho Classic H4 (0.026″ B-L slot, passive), Ormco Damon Q (0.028″ B-L slot, passive), and In-Ovation R (0.028″ slot, active) brackets were tested using 0.017″ × 0.025″ and 0.019″ × 0.025″ beta-titanium archwires. An in vitro orthodontic torque simulator (OTS) was used to rotate archwires relative to a single bracket while recording forces and moments in three directions. For each bracket-archwire combination, a total of n = 47 samples were tested. Repeated measures analysis of variance between brackets was conducted for third-order torque values at 3° increments between 9° and 30° during loading and unloading for each archwire size. Results: Statistically significant differences between H4 and Q brackets were only found for 0.017″ × 0.025″ archwires during loading, and 0.019″ × 0.025″ archwires during unloading. Conversely, differences between H4 and R brackets were found for both archwires during loading and unloading phases. Finally, when using a 0.017″ × 0.025″ archwire the H4 brackets reached the 5 Nmm threshold before R and Q brackets; however, there was little difference found when using a 0.019″ × 0.025″ archwire. Conclusions: The concept of using a smaller B-L bracket slot dimension in orthodontic treatment showed it may theoretically allow for more options, primarily using smaller archwires to correct third-order rotational misalignments. However, it is suspected that bracket material limitations and added loading on the door currently prevent this from being clinically applicable.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".