Root Canal Morphology of Permanent Mandibular Premolars in Iranian Population: A Systematic Review.
Bibliographic record
Abstract
INTRODUCTION: It is essential for clinicians to have knowledge about root canal configuration, although its morphology varies largely in different ethnicities and even in different individuals within the same ethnic group. The current study reviewed the root canal configuration of root canals in mandibular first and second premolars among Iranian population based on independent epidemiological studies. METHODS AND MATERIALS: A comprehensive search was conducted on retrieved articles related to root canal configuration and prevalence of each types of root canal in mandibular premolars based on Vertucci's classification. An electronic search was conducted in Medline, Scopus and Google Scholar from January 1984 to September 2015. RESULTS: In eleven studies conducted in eight provinces, 1644 mandibular first premolars and 1268 second premolars were investigated. Within mandibular first premolars, 70.9% were Vertucci's type I, followed by 10.4% type III, 7.18% type IV, 5.23% type II and 5.16% type V. In addition, among mandibular second premolars, 82.86% were type I, 6.25 type III, 5.32% type II, 4.27% type IV, and 0.69% type V. CONCLUSION: These results highlight the necessity of searching for additional possible root canals by clinicians. Moreover, these results indicated the ethnical characteristics of Iranian population regarding the morphology of mandibular premolars compared to other populations.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".