Bibliographic record
Abstract
Aim: The aim of this study was to evaluate and compare the beverages effect on the microhardness of composite and compomer direct restorative materials in comparison with mineral water. Materials and methods:Two types of direct restorative materials of A3 shade were selected for this study: Composan Bio-esthetic Nano-ceram Composite (PROMEDICA) and Composan compomer (PROMEDICA).Forty specimens were prepared from each restorative material (total number of specimens were 80).Each specimen was prepared by compressing a sufficient amount of material into a mold of 4 mm in diameter and 2 mm in thickness by two glass slides with acetate celluloid strip in between and curing the specimen for 20 seconds from only the top surface by making the curing tip in intimate contact with the acetate celluloid strips covering the composite and compomer surface with LED Woodpacker light curing unit.The top and bottom surfaces were divided into two halves: 1st half was subjected to microhardness testing before immersion, while microhardness testing was performed on the 2nd half after immersion in beverages.PH values were recorded for each beverage solution with pH meter (Mettler Toledo, Canada).Vickers microhardness testing was performed with a microhardness tester (Microhardness tester FM-800, Future-Tech, Japan) at 300 g load and 15 seconds according to ISO 4049 for both top and bottom surfaces by making three indentations and considering the mean microhardness value for each surface to be the Vickers hardness number for that surface.Three types of beverages were used in the study (Coca Cola, orange juice, Red Bull) and a fourth immersion solution of mineral water was used as a control group.The 80 specimens were immersed for 30 days at 37°C.The immersion solutions were replaced in a daily manner.After immersion, the composite and compomer specimens were incubated in distilled water at 37°C for 24 hours before the microhardness testing.Data were statistically analyzed before and after immersion of the 80 specimens using mean, standard deviation, one way ANOVA and t-test at a 5% level of significance.Results: One-way analysis of variance (ANOVA) for VHN composite top, bottom, and compomer top, bottom revealed that there was a statistically significant difference (p ≤ 0.05).t-tests comparing all the groups before and after immersion showed that there were statistically significant differences (p ≤ 0.05) in all groups being tested in this study.pH values for all the solutions were recorded as the followings: pH for Cola was 1.87, orange juice was 2.63, Red Bull was 2.55 and for water was 6.96.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".