A Comparison of Caries Rates in Non-Institutionalized Individuals With and Without Down Syndrome
Bibliographic record
Abstract
The caries rate of people with Down syndrome (DS) was compared to an age-matched control population without DS. A cross-sectional study design was used. Caries rates were assessed by an adjusted DFT score, expressed as a proportion of number of teeth in the mouth, to control for hypodontia in the subjects with DS. Bivariate and multiple linear regression analyses were used to compare caries rates in persons with and without DS. The sample size was 128, in which 44 were subjects with DS and 84 were subjects without DS. On a range of 0-1, the mean adjusted DFT scores were 0.10 in subjects with DS and 0.18 in the control group. Although this difference was significant at the bivariate level of analysis, in the multiple linear regression model, adjusted DFT was associated with age and professional fluoride therapy only. When expressed as a proportion of number of teeth, caries rates were not different in people with and without DS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".