Potential to induce dentinal cracks during retreatment procedures of teeth treated with “Russian red”: An ex vivo study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare the impact of treatment procedures on roots previously treated with resorcinol-formaldehyde resin and analyze the effectiveness of dye and magnification for the detection of dentin cracks. MATERIALS AND METHODS: Distal roots of 80 permanent first mandibular molars with a single canal were sectioned at 3mm and 9mm from the anatomical apex. Two groups were formed according to the method used for root canal penetration: group 1 (K-file and Pro Taper instruments) and group 2 (Ultrasound with Pro Ultra and Pro Taper files). Before and after the completion of procedures, photographs of the roots were taken for examination for cracks or/and infraction lines with two levels of magnification and with or without a dye. RESULTS: In groups 1 and 2, either with dye or without it, there were statistically significant differences (P<0.001) with more fractures observed in the coronal than in the apical part of specimens. Statistically significant proportional differences regarding the location of fractures were observed at both magnifications. When the dye was used, there were no statistically significant differences between the two magnifications in the detection of cracks. In the specimens where the dye was not used, differences between the groups were statistically significant at both magnifications with more complete and intra-dental fractures observed in group 2. CONCLUSIONS: Retreatment methods had a damaging effect on the root dentin of teeth previously treated with resorcinol-formaldehyde resin. At magnification ×16, the efficacy of using the dye for the detection of cracks was higher than detection without the dye.
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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) | 0.000 | 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 | 0.001 | 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".