Deformation and warping of the bracket slot in select self-ligating orthodontic brackets due to an applied third order torque
Bibliographic record
Abstract
OBJECTIVE: To measure the plastic deformation of three different self-ligated brackets as a result of third order torque by analysing slot dimensions and determine its impact on torque play. METHODS: Three different self-ligating orthodontic brackets (0·022-inch slot) were investigated: Damon Q®, In-Ovation R®, and Speed® (30 per group). A digital SLR camera coupled to a microscope was used to capture images of the slot profile of each bracket before and after torquing. Each bracket was torqued to 63° in the same manner using a 0·019×0·025-inch SS wire. RESULTS: The mean change in slot height as measured at the top of the slot was 0·013 mm (SD 0·020), 0·007 mm (SD 0·010) and 0·070 mm (SD 0·03) for Damon Q®, In-Ovation R® and Speed®, respectively. Slot taper increased 0·75° (SD 0·96), 0·41° (SD 1·05) and 9·30° (SD 4·24), respectively. Increase in torque play was calculated to be 0·9, 0·6 and 7·7° respectively, as calculated using the novel formula presented in this study. CONCLUSIONS: Damon Q® and In-Ovation R® maintain high levels of linearity in the shape of the slot walls and experience small, but significant amounts of plastic deformation that are physically insignificant. Speed® demonstrates the most plastic deformation with visually identifiable warping in the bracket slot.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".