Does the ideal health care system exist? Will it be accepted in Canada?
Bibliographic record
Abstract
Let’s face it, surgery is expensive, resource intensive and complex. In most Canadian provinces, health care has assumed >50% of the overall provincial budget and these costs show no signs of falling. On a cursory count, at least one dozen separate processes need to dovetail for a surgical procedure to occur, including a suitable infrastructure (preoperative, operative, recovery), appropriate equipment, adequate human resources (nursing, anesthesia, surgery and support staff) and aligned patient variables (correct indication, informed consent, fasted, etc). In the United States, health systems leverage the operating room as a profit centre, passing these costs to the insurer, while in Canada (and other socialized health care systems), the operating room is the most expensive cost centre in any facility. Currently, the United States leads the world in health care spending, which has surpassed 17% of gross domestic product (GDP). Although not as high in Canada, health care spending was approaching 12% of GDP. Throughout the world, many surgical techniques have been standardized, with reportable standardized outcomes related to the specific surgery. Little comparative data are available to evaluate the system providing the resources for the reconstructive surgeon and their patients. As these health delivery systems evolve, the question as to what is ideal continually arises.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".