High caries prevalence and risk factors among young preschool children in an urban community with water fluoridation
Bibliographic record
Abstract
BACKGROUND: Singapore is unique in that it is a 100% urban community with majority of the population living in a homogeneous physical environment. She, however, has diverse ethnicities and cultures as such; there may be caries risk factors that are unique to this population. AIM: The aims were to assess the oral health of preschool children and to identify the associated caries risk factors. DESIGN: An oral examination and a questionnaire were completed for each consenting child-parent pair. RESULTS: One hundred and ninety children (mean age: 36.3 ± 6.9 months) were recruited from six community medical clinics. Ninety-two children (48.4%) were caries active. The mean d123 t and d123 s scores were 2.2 ± 3.3 and 3.0 ± 5.6, respectively. Higher plaque scores were significantly (P < 0.0005) associated with all measures of decay (presence of decay, dt, ds). The risk factors for severity of decay (i.e., dt and ds) include child's age, breastfeeding duration, and parents' ability to withhold cariogenic snacks from their child. CONCLUSIONS: The high caries rate suggests that current preventive methods to reduce caries in Singapore may have reached their maximum effectiveness, and other risk factors such as child's race, and dietary and breastfeeding habits need to be addressed.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".