Polymerization with a micro-xenon light of a resin-modified glass ionomer: a shear bond strength study 15 minutes after bonding
Bibliographic record
Abstract
The purpose of this study was to evaluate the initial shear bond strength (15 minutes after bonding) of a resin-modified glass ionomer (RMGIC, Fuji Ortho LC) cured with two different light-curing units: a conventional visible light (Ortholux XT) and a microxenon light (Aurys). Seventy-five freshly extracted bovine permanent mandibular incisors were randomly assigned to one of five groups; each group consisted of 15 specimens. Group A (Transbond XT) and group B (Fuji Ortho LC) were exposed to the visible light for 20 and 40 seconds, respectively, and used as controls. The remaining three groups (C, D, and E) were bonded with Fuji Ortho LC and cured with Aurys for 10, 5, and 2 seconds, respectively. All samples were tested in a shear mode on an Instron universal testing machine 15 minutes after bonding. The shear bond strength of the control group bonded with Transbond XT was significantly higher (P = 0.000) than those of all the other groups tested. Regarding Fuji Ortho LC, no statistically significant differences were found between the bond strength of the control group cured with Ortholux XT, and those of the groups cured with Aurys for 2, 5, and 10 seconds. The present findings indicate that, compared with visible light-curing, the micro-xenon light enables the clinician to significantly reduce the curing time of RMGICs, without affecting their initial shear bond strengths.
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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 | 0.000 |
| 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) | 0.003 | 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".