Effect of an internal coating technique on tensile bond strengths of resin cements to zirconia ceramics
Bibliographic record
Abstract
This study was conducted to enhance the tensile bond strengths of resin cements to zirconia ceramics. Fifty-six zirconia ceramic specimens (Cercon Base) and twenty-eight silica-based ceramic specimens (GN-1, GN-1 Ceramic Block) were air-abraded using alumina. Thereafter, the zirconia ceramic specimens were divided into two subgroups of 28 each according to the surface pretreatment; no pretreatment (Zr); and the internal coating technique (INT). For INT, the surface of zirconia was coated by fusing silica-based ceramics (Cercon Ceram Kiss). Ceramic surfaces were conditioned with/without a silane coupling agent followed by bonding with one of two resin cements; Panavia F 2.0 (PF) and Superbond C&B (SB). After 24 hours storage in water, the tensile bond strengths were tested (n=7). For both PF and SB, silanization significantly improved the bond strength to GN-1 and INT (p<0.05). The INT coating followed by silanizaton demonstrated enhancement of bonding to zirconia ceramics.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".