ICES Reports: Chronic Complications of Diabetes: Cardiovascular and Kidney Disease
Bibliographic record
Abstract
Diabetes mellitus is a serious and growing health problem.Approximately 6% of Ontarians are diagnosed with diabetes (Hux et al. 2002), however, with the aging of the population and growing rates of obesity, the numbers with this condition are expected to rise (Mokdad et al. 2001).Canadian researchers place the economic burden of diabetes at an estimated $7 billion nationwide based on 1998 figures (Dawson 1998).The largest proportion of expenditures relating to diabetes has been attributed to in-patient costs.Diabetes is a leading cause of cardiovascular disease (Rubin et al. 1992), blindness (Klein and Klein 1995), end-stage renal failure leading to dialysis (Nelson et al. 1995), and amputation (Bild et al. 1989).To examine this further, scientists at the Institute for Clinical Evaluative Sciences (ICES) conducted a series of studies to quantify the burden of diabetes and its associated complications in Ontario.Module 2 of Diabetes in Ontario: An ICES Practice Atlas, focuses on rates of chronic complications related to this condition.In this report, findings from analyses of cardiac complications and dialysis rates among persons with diabetes are highlighted.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.009 |
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".