The influence of canal patency on the success of root canal treatment
Bibliographic record
Abstract
Introduction: Treatment involving complete obliteration of root canal system requires extensive analysis, both because of numerous existing clinical problems involved and limited research conducted in this area.Objectives: The objective of the study was to provide a comparative clinical and radiological evaluation of two gutta-percha obturation methods applied in root canal treatment in conditions of total obliteration: lateral condensation versus continuous wave condensation technique.Material and methods: A total of 310 teeth from 121 patients were analyzed.Overall, 35 teeth contained various degree of root canal calcification.A comparison was made between the following two obturation techniques: lateral condensation method and continuous wave of condensation approach (taking into account the existence of periapical lesions, and whether the patient was undergoing primary treatment or re-treatment).Results: The healing process in the case of two root canal obturation method depended on the number of variables, such as the presence of obliteration (p < 0.001) and CWC treatment method selected (p = 0.018). Conclusions:The positive treatment outcomes achieved with the CWC method suggest that this thermal technique should be the treatment of choice when obliterations occur and in the absence of patency in the apical part of the root canal.
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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 | 0.007 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".