A comparison of dynamic and static testing of latex and nonlatex orthodontic elastics.
Bibliographic record
Abstract
The purpose of this study was to determine the effects of repeated stretching (cyclic testing) and static testing on the force decay properties of two different types of orthodontic elastics from a single supplier. Samples of American Orthodontics' 0.25 inch, 4.5 oz (6.35 mm, 127.5 g) latex and nonlatex elastics were used and a sample size of 12 elastics per group was tested. Static testing involved stretching the elastics to three times marketed internal diameter (19.05 mm) and measuring force levels at intervals over 24 hours. Cyclic testing used the same initial extension but cycled the elastics an additional 24.7 mm to simulate extension with maximal opening in the mouth. Both types of elastic had similar initial forces that were statistically below the marketed force (122 and 118 g for latex and nonlatex elastics, respectively) at three times marketed internal diameter. Cyclic testing caused significantly more force loss and this difference occurred primarily within the first 30 minutes. For statically tested elastics the percentage of initial force remaining at 4, 8, and 24 hours was 87%, 85%, 83%, and 83%, 78%, 69% for latex and nonlatex elastics, respectively. For cyclically tested elastics the percentage of initial force remaining at 4, 8, and 24 hours was 77%, 76%, 75%, and 65%, 63%, 53% for latex and nonlatex elastics, respectively.
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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 | 0.002 | 0.004 |
| 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) | 0.004 | 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".