Development of New Methods and Materials for the Restoration of Tooth Pulp
Bibliographic record
Abstract
Nowadays, the latest treatment technologies are actively developing in dental practice, namely for the restoration of tooth pulp. Aim: to evaluate the advantages of using modern materials in the treatment of tooth pulps. Materials and Methods: We examined 33 patients with pulp diseases: 18 women (54.5%) and 15 men (45.5%) with an average age of (33.2±2.3) years. 18 patients (group I) had conservative treatment; 15 patients (group II) got pulp restoration using Biodentin. Results: In 33 (100 %) patients of both groups, inflammation of tooth pulps was found; in 5 of 18 (27.8 %) patients of group I and 6 of 15 (40.0 %) patients of group II, the presence of fibrous pulpitis without signs of periodontitis was determined, in patients of group II, 4 of 15 (26.7 %) - acute diffuse pulpitis. Streptococci with α-haemolytic activity, staphylococci and fungi of the genus Candida albicans were detected in the plaque. In 93.3% of patients, both clinical and overall success was achieved with Biodentin, and the frequency of isolation of microorganisms of the genus Streptococcus spp. with α-haemolytic activity and Candida albicans decreased. Conclusions: Effective pulp restoration, inflammatory process reduction, and conditionally pathogenic microflora suppression were found in patients treated with Biodentin.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".