Comparative Study of Dental Care and Dental Services in Iran and Selected Countries
Bibliographic record
Abstract
Objective: The purpose of this research is a comparative study of dental care and dental services as practiced in Iran, Canada, the United States, Sweden, and Turkey. Basic research design: A comparative study was conducted. Canada, the United States, and Sweden were selected due to a continued decline in dental caries index from 1970 to 2010. Turkey and Iran were selected because of the similarities in their indicators. To compare the countries, database of the World Health Organization database of dental oral health indicators was used. Main outcome measures: The indicators relating to dental care and dental services listed in the World Health Organization database were collected and analyzed. Compared with the other selected countries, Iran was found to enjoy a good status in the prevalence of dental caries. Results: limited free treatment to available groups, mal distribution of dentists, dental hygienists shortages, high costs of direct payment and a lack of good insurance coverage for dental care and dental services in the field of dental care and dental services Lack of equity in access to appropriate dental services. Conclusion: An improvement in the country's dental care is required. It turned out that interventions in the areas of insurance coverage in the country, creating insurance funds for dental care, educating students on dental care in schools and families, and training dental hygienists, particularly in underserved areas would be useful measures to take in the future to prevent the increased tooth decay index.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".