Bibliographic record
Abstract
Clinical studies suggest that smokers have a higher than average risk of periodontal disease and poor oral health status. In 2003, the Canadian Community Health Survey--a multistage, nationwide household survey--asked a series of questions related to oral health status. This report is based on the population aged 18 and older who answered the optional module on oral health (33,777 respondents). This subsample represents a weighted population of 23.9 million. The overall survey response rate was 80.6%.In our sample, 24% of respondents were current cigarette smokers, 43% were former smokers and 33% had never smoked. The prevalence of current smoking declined with advancing age and was inversely associated with household income and level of education. The prevalence of edentulism was 15% among current smokers compared with 7% among those who had never smoked. In the dentate population, current smokers were less likely to have visited a dentist in the past 3 years and more likely to report sensitivity of teeth, tooth ache in the previous month, pain in the mouth or face and social limitations because of teeth. When age, sex, household income and dental insurance were controlled in a multivariate logistic regression model, current smokers and former smokers had higher odds of reporting oral-facial pain than people who had never smoked. Prevention of smoking onset and support for cessation of smoking could contribute to improved oral health status.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".