Characterization of an Experimental Two-Step Self-Etch Adhesive’s Bonding Performance and Resin-Dentin Interfacial Properties
Bibliographic record
Abstract
This study evaluated an experimental two-step self-etch adhesive (BZF-29, BZF) by comparing it with a reference two-step self-etch adhesive (Clearfil Megabond 2, MB) and a universal adhesive (G-Premio Bond, GP) for microtensile bond strength (μTBS) and resin-dentin interfacial characteristics. Twenty-four human third molars were used for the μTBS test. Bonded peripheral dentin slices were separated to observe the resin-dentin interface and measure the adhesive layer thickness with SEM. μTBS data of the central beams were obtained after 24 h and 6 months of water storage. Fracture modes were determined using a stereomicroscope and SEM. Nine additional third molars were used to determine the elastic modulus (E) employing an ultra microhardness tester. Water storage did not affect μTBS of the tested adhesives (p > 0.05). μTBS of BZF and MB were similar but significantly higher than GP (p < 0.05). BZF achieved the highest adhesive layer thickness, while GP the lowest. E of BZF and MB were comparable but significantly lower than GP (p < 0.05). Except for GP, the predominant fracture mode was nonadhesive. The superior bonding performance of BZF and MB could be attributed to their better mechanical property and increased adhesive thickness imparting better stress relief at the interface.
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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) | 0.001 | 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".