Fracture resistance of bleached teeth restored with different procedures
Bibliographic record
Abstract
This study evaluated the fracture resistance of teeth submitted to internal bleaching and restored with different non-metallic post. Eighty mandibular incisors were endodontically treated and randomly divided in 10 groups (n = 8): G1- restored with composite resin (CR), G2- CR + fiber-reinforced composite post (FRC, Everstick post, Sticktech) cemented with resin cement self-etch adhesive (RCS, Panavia F 2.0, Kuraray), G3- CR + FRC + self-adhesive resin cement (SRC, Breeze, Pentral Clinical), G4- CR+ glass fiber post (GF, Exacto Post, Angelus) + RCS, G5- CR + GF + SRC. The G6 to G10 were bleached with hydrogen peroxide (HP) and restored with the same restorative procedures used for G1 to G5, respectively. After 7 days storage in artificial saliva, the specimens were submitted to the compressive strength test (N) at 0.5 mm/min cross-head speed and the failure pattern was identified as either reparable (failure showed until 2 mm below the cement-enamel junction) or irreparable (the failure showed <2 mm or more below the cement-enamel). Data were analyzed by ANOVA and Tukey test (α = 0.05). No significant difference (p < 0.05) was found among G1 to G10. The results suggest that intracoronal bleaching did not significantly weaken the teeth and the failure patterns were predominately reparable for all groups. The non-metallic posts in these teeth did not improve fracture resistance.
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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 | 0.000 | 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".