Associação entre discriminação racial e cárie dentária em adolescentes
Bibliographic record
Abstract
Objective: To identify the association between the presence of racial discrimination and the oral health situation related to tooth decay. Method: Cross-sectional study, with a sample of 209 adolescents, evaluated in a school environment through the application of a questionnaire and clinical oral examination. The variables were perceived racial discrimination, sociodemographics, tooth decay (presence of at least one decayed tooth). Data were analyzed using Pearson's Chi-square or Fisher's exact tests and Multiple Logistic Regression. Results: The majority of adolescents were black (66%), female (56.2%), aged between 14 and 16 years old (56%), heterosexual (73.2%) and Christian (59.3%) . Regarding socioeconomic situation, 41.1% received a family allowance and 19.2% had a family income of up to one minimum wage. Most respondents had cavities (97.5%) and around a quarter lost some permanent teeth. There was an association between race/color according to IBGE (p=0.033) and skin color scale (p=0.012) and the occurrence of tooth decay. Black adolescents were twice as likely to have tooth decay (OR=2.11; CI=1.08-4.15). Conclusion: The findings of this study allow us to conclude that an association was observed between racial discrimination and tooth decay.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".