Microleakage of Class V composites using different placement and curing techniques: an in vitro study.
Bibliographic record
Abstract
PURPOSE: To evaluate microleakage at enamel and dentin margins of two composite resins, using bulk and incremental placement techniques, "rebonding", and facial and lingual curing methods. MATERIALS AND METHODS: One hundred standardized Class V cavity preparations were made on the facial surface of extracted human premolars and were randomly assigned to 10 groups. Single Bond was used as the dentin/enamel adhesive. A heavily filled composite resin, Z250, and a microfill, Silux Plus, were inserted and polymerized using five different techniques: (1) incremental placement and facial curing; (2) incremental placement, facial curing and rebonding; (3) bulk placement and facial curing; (4) bulk placement, facial curing and rebonding; (5) incremental placement and lingual and facial curing. After the restorations were finished and polished, the margins of those in the rebonded groups were etched, rinsed, and dried. The adhesive resin, Single Bond, was applied at the composite resin-tooth interface and light-cured. All the specimens were thermocycled, stained with 1% methylene blue, sectioned, and evaluated for leakage (0-4 scale) by two examiners. RESULTS: Almost no leakage occurred at enamel margins. At the cementum margins, differences in microleakage related to restorative material or technique were not statistically significant. However, leakage at the cementum margins was significantly greater than at the enamel margins for both composite resin materials.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".