The Effect of Funding Cuts on the Utilization of an Oral Pathology Diagnostic Service
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
AIM: To examine what impact the loss of funding had on the utilization of the oral pathology service. METHODOLOGY: Biopsy records were retrieved and examined in the two year period before and after the elimination of the subsidies in 2003. RESULTS: After the loss of funding, there was a 31% decrease in the number of specimens submitted from practitioners in private practice, with the greatest drop noted in submissions from endodontists. CONCLUSION: Despite the immediate decrease in the number of biopsies submitted after the introduction of fee-for-service, the number of specimens being submitted appears to be on the rise again, as practitioners appear to recognize the value of a specialized oral pathology diagnostic service.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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