Prevalence of Mucosal Lesions in People Consuming Chewable Tobacco in Hormozgan Province, Iran
Bibliographic record
Abstract
Background: Tobacco has a high level of carcinogenic components. The maximum effect of the component is on the oral cavity and the location of tobacco. Quantitative studies were conducted according to the oral effect of tobacco usage by people of the south of Iran, specifically in Hormozgan province. In this experiment, the prevalence of oral lesions was studied in people who use tobacco in Hormozgan province in 2018. Materials and Methods: In this descriptive cross-sectional study, 395 patients were examined on oral lesions in Hormozgan province. Data were collected and described by a mean frequency table and then analyzed by an inferential statistical test such as the 2-dimensional chi-square test by SPSS, version 23 (P<0.05). Results: Experiments showed that 75.5% (299 from 395) of patients had mucosal lesions. The most lesions were tobacco pouch, wound, white plaque, and erythematic lesions. In addition, a significant correlation was found among parameters, including all mucosal lesions with time, all mucosal lesions with age (except wound), white plaque and erythematic mucosal lesions with smoking, tobacco pouch, and white plaque with alcohol use. However, no significant correlation was observed between oral mucosal lesions with a history of family oral lesions, tobacco pouch and wound with cigarette usage, and wound and erythematic lesions with alcohol use. Conclusion: Compared with other studies, oral mucosal lesions were highly prevalent in Hormozgan province. The possibility of oral mucosal lesions increases as one gets older; in addition, the duration of tobacco usage is a primary factor for the lesions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".