Effect of ionizing radiation and chewing simulation on human enamel and zirconia
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To evaluate the effect of ionizing irradiation on human enamel and zirconia after chewing simulation. METHODS: Twenty enamel and twenty translucent Yttria-stabilized zirconia (Y-PSZ) specimens were divided in 4 groups: Co (control) - no irradiation on enamel cusps/opposing zirconia slabs; E70 - irradiated (70 Gray) enamel cusps/opposing irradiated enamel slabs; Z70 - irradiated zirconia cusps/opposing irradiated zirconia slabs; EZ70 - irradiated enamel cusps/opposing irradiated zirconia slabs. Cusps were abraded against slabs in a chewing simulator (CS - one million cycles, 80 N, artificial saliva, 37˚C). Wear and roughness of zirconia and enamel were analyzed using a stylus profilometer. The abraded enamel was analyzed by Electron probe micro-analyzer (EPMA) and zirconia was characterized by nanoindentation and X-ray diffraction. One-way analysis of variance (ANOVA) and Tukey test were used for analysis of wear, Repeated Measures and Bonferroni test for roughness, and hardness and modulus values were compared using Wilcoxan Mann Whitney rank sum test (overall 5% significance). RESULTS: Significantly higher volume loss was presented by cusps in the E70 group (p<0.001). Wear was similar between Co and EZ70 groups. There was no significant effect of irradiation on roughness of enamel or zirconia slabs (p=0.072). Irradiated Y-PSZ slabs had significantly higher hardness and modulus than non-irradiated ones and a 7% increase in m phase content was detected after irradiation. CONCLUSIONS: The opposing surface characteristics played a more significant role on enamel wear than did ionizing radiation. However, radiation affects Y-PSZ crystalline composition, hardness and modulus of elasticity.
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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 | 0.003 | 0.001 |
| 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 it