Effect of preheating on microhardness and viscosity of 4 resin composites.
Bibliographic record
Abstract
OBJECTIVE: This study was undertaken to determine the effect of temperature on the microhardness and viscosity of 4 resin composite materials. METHODS: To investigate microhardness, samples of each of the 4 composite materials, prepared by standard insertion of resin into prefabricated moulds, were divided into 2 groups (n = 10 per group). On the first group, the resin composite materials were inserted into the moulds at room temperature and cured. On the second group, the resin composite materials were pre-heated in a heating device, inserted into the moulds and immediately cured. Microhardness after curing (both immediately and after 24 hours of storage) was determined (using a 300 g load applied for 10 seconds) and averaged for 5 randomly selected points on the top and bottom surfaces of each sample. To investigate viscosity, 0.5 g samples of room temperature or preheated resin composite (n = 15 per group) were placed under a 454 g load for 45 seconds before light-curing (40 seconds). After curing, each sample was photographed and the surface area calculated. Data were analyzed by t tests or one-way analysis of variance and Tukey's test. RESULTS: Preheating the resin composites increased the microhardness and decreased the viscosity of the samples. Filtek Supreme Ultra resin composite had the highest mean microhardness, and Vit-l-escence resin composite had the lowest viscosity. CONCLUSIONS: The effects of preheating resin composites may allow easier placement of restorations and greater monomer conversion.
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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 | 0.000 | 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".