Effect of Artificial Aging Protocols on Bond Strength Between Orthodontic Metallic Brackets and Human Enamel
Bibliographic record
Abstract
Background: Limited studies compare artificial aging methods simulating oral environment on orthodontic brackets. Objectives: To evaluate the effect of in vitro aging protocols on bond strength between bracket and enamel, and to evaluate enamel loss as a function of aging. Methods: Sixty upper premolars with bonded metallic brackets were divided into 4 groups (n=15): Control (CO) - distilled water storage for 21 days; Thermocycling (TC) - 20,000 thermocycles; Mechanical cycling (MC) - 10,000 chewing cycles; Thermo-mechanical cycling (TMC) - TC+MC and subjected to shear bond strength testing (SBS). Adhesive remnant on enamel was assessed with stereomicroscope. Presence of calcium and phosphorus on the bracket was examined with scanning electron microscopy. Results: SBS values of TC and TMC were lower than CO (p<0.05). There was no difference for percentage of adhesive remnant (p>0.05) and enamel loss. Conclusion: Artificial aging protocols with TC or TMC decreased SBS of metallic brackets to enamel.
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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 | 0.001 |
| 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) | 0.002 | 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".