Knoop hardness of five composites cured with single-peak and polywave LED curing lights.
Bibliographic record
Abstract
OBJECTIVE: As resin-modified glass-ionomer cement (RMGIC) is an adhesive material, its association to dentin bonding agents (DBAs) was previously proposed. This study investigated the adjunctive behavior of an RMGIC with etch-and-rinse bonding systems under in situ/ex vivo cariogenic challenge. METHOD AND MATERIALS: Bovine enamel blocks (3 3 3 3 2 mm) were randomly assigned to group VP, Vitremer + its own primer (3M ESPE); group VSB, Vitremer + Single Bond (3M ESPE); and group VPB, Vitremer + Prime and Bond 2.1 (Dentsply). Two blocks of each group were randomly placed in an acrylic palatal appliance, so each appliance included six blocks. Volunteers (n = 10) wore these appliances according to given instructions to promote a sucrose challenge eight times/day for 15 days. After this period, the blocks were removed from the devices and cleaned, and demineralization was assessed through longitudinal microhardness analysis (Knoop indenter, 25 g/5 s). Data were submitted to three-way ANOVA and Tukey test (P < .05). RESULTS: No treatment was able to completely avoid demineralization. All materials showed a statistically significant difference in mineral loss when the microhardness on the outer enamel was compared with deeper regions (P < .05). CONCLUSION: Association of the tested RMGICs with etch-and-rinse DBAs did not seem to be more beneficial against caries than the conventional treatment with RMGIC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".