Effect of Precuring Warming on Mechanical Properties of Restorative Composites
Bibliographic record
Abstract
To investigate the effect of prepolymerization warming on composites' mechanical properties, three composites were evaluated: Clearfil Majesty (CM) (Kuraray), Z-100 (3M/ESPE), and Light-Core (LC) (Bisco). Specimens were prepared from each composite at room temperature as control and 2 higher temperatures (37°C and 54°C) to test surface hardness (SH), compressive strength (CS), and diametral tensile strength (DTS). Data were statistically analyzed using ANOVA and Fisher's LSD tests. Results revealed that prewarming CM and Z100 specimens significantly improved their SH mean values (P < 0.05). Prewarming also improved mean CS values of Z100 specimens (P < 0.05). Furthermore, DTS mean value of CM prepared at 52° was significantly higher than that of room temperature specimens (P < 0.05). KHN, CS, and DTS mean values varied significantly among the three composites. In conclusion, Prewarming significantly enhanced surface hardness of 2 composites. Prewarming also improved bulk properties of the composites; however, this improvement was significant in only some of the tested materials.
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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".