Prevalence of Geographic tongue and Related Predisposing Factors in 7-18 Year-Old Students in Kermanshah, Iran 2014
Bibliographic record
Abstract
Geographic tongue is a benign lesion at the dorsum and margins of the tongue that sometimes causes pain and burning sensation. This lesion is characterized by an erythematous area with white or yellow folded edges. The predisposing factors of this lesion include heredity, allergies, psoriasis, stress, fissured tongue and consumption of some foods. The present study was conducted to investigate the prevalence of geographic tongue and its related factors among the 7-18 year-old students in Kermanshah, Iran. This descriptive cross-sectional study was carried out in three schools in Kermanshah using multi-stage random cluster sampling method. A total number of 3600 students were examined (1800 girls and 1800 boys). Demographic data and the results of examinations were recorded in a questionnaire. The factors affecting the incidence of geographic tongue were analyzed by the SPSS-20 software and the Chi-square test.The prevalence of geographic tongue was 7.86% (283 individuals). The incidence of this lesion was significantly higher in males than in females (p<0.01). There was no relationship between geographic tongue and psoriasis or fissured tongue. Pain and discomfort during eating was more prevalent in those with geographic tounge compared to those without this condition (p<0.02). The prevalence of geographic tongue among the studied population was 7.86%, and the prevalence of geographic tongue in male students was higher than in female students.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".