A comparison of the dental health of Brazilian and Canadian independently living elderly
Bibliographic record
Abstract
OBJECTIVE: To compare the dental status of Brazilian and Canadian elderly populations with respect to socioeconomic and quality of life factors. MATERIALS AND METHODS: A total of 496 adults aged 60-75 years, having four or more teeth, and physically and cognitively suitable for a clinical oral examination were included. Subjects answered questions concerning their lifestyle and completed the Geriatric Oral Health Assessment Index (GOHAI) questionnaire. RESULTS: In all populations, the majority were females, aged between 60 and 65 years and married. Although the Canadian New Immigrant population had lower mean income, they had more remaining teeth (23.04 ± 6.1), more functional teeth (sound and restored teeth) (14.92 ± 5.7), more sound teeth (15.40 ± 7.6), but more carious teeth (2.97 ± 3.0). The Brazilian population had higher numbers of restored teeth (12.26 ± 6.8) and fewer remaining teeth (17.80 ± 7.6). In all populations, females, married and younger (60-65 years old) adults were more likely to retain 20 or more teeth. The mean GOHAI scores were similar for Canadians (40.55 ± 5.7) and Canadian New Immigrants (39.28 ± 6.5), but were higher than that among Brazilians (31.97 ± 8.9). CONCLUSIONS: The numbers of remaining teeth were related to greater education and higher income status for Brazilian and Canadian populations. However, Canadian New Immigrants with lower income and education retained more teeth than the 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".