Effect of repeated heating and cooling cycles on the degree of conversion and microhardness of four resin composites
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the effect of repeatedly heating and cooling four resin-based composites (RBCs) for up to six cycles. MATERIALS AND METHODS: Four commercial RBCs were heated to 68°C and cooled to room temperature for up to six cycles before photocuring at 30°C. Specimens spent a total of 0, 30, 60, 90, 120, 150 min, or 7 days at 68°C. The degree of conversion (DC) was measured at the bottom of the specimens immediately after photocuring. The Vickers microhardness was measured at the top and bottom of the RBC surfaces 24 h after photocuring. The data were analyzed using one-way analysis of variance, Dunnett's or Bonferroni post-hoc tests, and Spearman correlation analysis (α = 0.05). RESULTS: For two brands of RBC, the DC decreased at various time points; however, these decreases were small, and there was no correlation (negative or positive) between the number of heating cycles and the DC for any of the RBCs. Repeated heated and cooling resulted in small changes in the hardness (compared to the control) in both directions (Dunnett; p < 0.05). Two of the RBCs showed a significant, positive correlation between the number of heating cycles and their hardness at the bottom surface. CONCLUSION: Repeated heating, cooling, and then reheating the RBCs for up to 1 week had little overall effect on their DC and microhardness values. The 2 mm thick specimens of all four RBCs achieved a bottom: top hardness ratio exceeding 0.8 after a 20 s exposure to light from a commercial LED curing light CLINICAL SIGNIFICANCE: Six repeated dry heating and cooling cycles of up to 1 week in duration had little effect on the DC and the microhardness of four commercial resin-based composites.
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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 | 0.000 |
| 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".