Variable Smear Layer and Adhesive Application: The Pursuit of Clinical Relevance in Bond Strength Testing
Bibliographic record
Abstract
The removal or modification of smear layers that cover the dentin is critical to allow the penetration of adhesive molecules and to ensure a strong bond between resin and dentin. Aiming to establish a model for clinically-relevant dentin-bond testing, we evaluated the effects of smear layers created by abrasives having similar coarseness (180-grit SiC paper; fine-grit diamond bur) and application modes (single application; double application) on the microtensile bond strengths (µTBS) of two currently available universal adhesives (G-Premio Bond; Scotchbond Universal Adhesive) and a two-step self-etch adhesive (Clearfil Megabond 2). Sixty extracted human third molars were used for the μTBS test. Data were analyzed by three-way ANOVA and Tukey’s test (α = 0.05). Fracture modes were determined using stereomicroscopy. An additional 24 third molars were prepared for observation of the resin–dentin interface by TEM and adhesive-smear layer interaction by SEM. μTBS was significantly affected by the adhesives and their application modes (p < 0.001), implying that the double application of universal adhesives should be recommended to improve their performance. The effect of smear layers was not significant (p > 0.05), indicating that 180-grit SiC papers could be used to prepare dentin as a substitute for fine-grit diamond burs for dentin-bond testing in laboratory settings.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".