Potentially Preventable Hospital Use for Dental Conditions: Implications for Expanding Dental Coverage for Low Income Populations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recently, attention has been placed on the issue of poor access to dental care, and the implications this may have for health care systems, in particular emergency department use for basic dental problems. In 2006, approximately 26,000 of 12 million Ontarians used acute-care hospital services for select dental problems, representing a cost of $16.4 million. There were 964 hospital admissions. The majority of use is by low-income adults. Although better access to dental care may lessen this burden on the health care system, the potential costs averted are considerably less than current proposals to improve access to dental care for low-income groups in Canada. Justifying renewed government investments in dental care in economic terms will require a broader assessment of costs; these data provide a starting-point for policymakers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it