A study of the frictional characteristics of four commercially available self-ligating bracket systems
Bibliographic record
Abstract
The objective of this investigation was to assess and compare the in vitro tribological behaviour of four commercially available self-ligating bracket systems. The frictional characteristics of the Damon3, Speed, In-Ovation R, and Time2 bracket systems were studied using a jig that mimics the three-dimensional movements that occur during sliding mechanics. Each bracket system was tested on the following stainless steel archwires: 0.016 x 0.022, 0.019 x 0.025, 0.020 round, and 0.021 x 0.021 inch Speed D-wire. An Instron testing machine with a 50 N load cell was used to measure the frictional resistance for each bracket/tooth assembly. The crosshead speed was set at a constant rate of 1 mm/minute, and each typodont tooth was moved along a fixed wire segment for a distance of 8 mm. Descriptive statistical analysis for each bracket/archwire combination with regard to frictional resistance was performed with a two-way, balanced analysis of variance for bracket type and wire size. The Damon3 bracket consistently demonstrated the lowest frictional resistance to sliding, while the Speed bracket produced significantly (P < 0.001) more frictional resistance than the other brackets tested for any given archwire. The self-ligation design (passive versus active) appears to be the primary variable responsible for the frictional resistance generated by self-ligating brackets during translation. Passively ligated brackets produce less frictional resistance; however, this decreased friction may result in decreased control compared with actively ligated systems.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".