Effect of Water Storage on the Flexural Strength of Four Self-etching Adhesive Resin Cements and on the Dentin-titanium Shear Bond Strength Mediated by Them
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Bibliographic record
Abstract
AIM: The aim of this study was to evaluate the effect of water storage on the flexural strength (σf) of four self-etching adhesive resin cements (SEARC) and on the dentin-titanium shear bond strength (SBS) mediated by them. MATERIALS AND METHODS: The selected SEARC were Rely X Unicem, G-Cem, Maxcem, and SmartCem2. For each material, 50 bars (2×2×25 mm) were made and stored in water at 37°C for 1 hour, 1 day, 7 days, 30 days, and 60 days before σf was determined via a three-point bend test. Titanium cylinders were bonded to freshly exposed human dentin surfaces using the selected cements. Fifty samples were obtained for each SEARC and were stored in water at 37°C for 1 hour, 1 day, 7 days, 30 days, and 60 days before SBS was determined. The results were statistically analyzed using two-way analysis of variance followed by Scheffé multiple means comparisons (α=0.05). Pearson's correlation coefficient between σf and SBS was determined. RESULTS: Significantly different σf and SBS values were obtained for the four cements. With regards to the effect of water storage, the σf of all materials increased during the first 7 days, was not significantly different between materials by 30 days, and then remained relatively constant or decreased for SmartCem2; SBS was not affected by water storage, with the exception of Maxcem, where a significant drop in SBS was detected after 1 day and no deterioration thereafter. No correlation was found between σf and SBS. CONCLUSIONS: Under the experimental conditions of this study, 60 days of water storage negatively affected the σf of SmartCem2 but did not negatively affect the SEARC-mediated dentin-titanium SBS (Maxcem showed a significant drop in SBS after 1 day but no deterioration thereafter). The dentin-titanium adherence afforded by Rely X and G-Cem was significantly higher than that of Maxcem and SmartCem2.
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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 | 0.000 |
| 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) | 0.001 | 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 it