Clinical-radiological study on the role of biostimulating materials in iatrogenic furcation lesions.
Bibliographic record
Abstract
UNLABELLED: Root perforation is an unwanted incident which may occur at any stage of endodontic treatment and can adversely affect tooth prognosis. AIM: To compare the recovery rate after treatment of root perforations in the interradicular area of the molars, using two different materials: MTA and ceramic nanoparticles mineral cement DiaRoot BioAggregate, by a clinical-radiological and statistical analysis over a period of up to 24 months. MATERIAL AND METHODS: The study was conducted on 28 molars from patients of both sexes, mean age 33.29 +/- 6.2DS, with iatrogenic perforation of pulp chamber floor. The teeth were divided into 2 groups according to the applied material: group 1--gray MTA (ProRoot MTA, Dentsply, Tulsa Dental), and group 2--BioAggregate (Diadent Group International, Vancouver). Patients included in the study were monitored and assessed by radiological examinations at 6, 12 and 18 months. RESULTS: Pulp chamber floor perforations are significantly associated with tooth location (chi2 = 35.60, r = 0.67, p = 0.00359, 95% CI). Both when the perforation was repaired with MTA and BioAggregate, the clinical improvement was significant (chi2 = 17.608, r = 0.58, p = 0.0035, 95% CI). CONCLUSIONS: Based on the results of this study, both MTA and BioAggregate are excellent materials for root perforation repair.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".