Bibliographic record
Abstract
HEALTH ISSUE: Diabetes mellitus (DM) is a chronic health condition affecting 4.8% of Canadian adults >/= 20 years of age. The prevalence increases with age. According to the National Diabetes Surveillance System (NDSS) (1998-1999), approximately 12% of Canadians aged 60-74 years are affected. One-third of cases may remain undiagnosed. The projected increase in DM prevalence largely results from rising rates of obesity and inactivity. KEY FINDINGS: DM in Canada appears to be more common among men than women. However, among Aboriginal Canadians, two-thirds of affected individuals are women. Although obesity is more prevalent among men than women (35% vs. 27%), the DM risk associated with obesity is greater for women. Socio-economic status is inversely related to DM prevalence but the income-related disparities are greater among women. Polycystic ovarian syndrome affects 5-7% of reproductive-aged women and doubles their risk for DM. Women with gestational diabetes frequently develop DM over the next 10 years. DATA GAPS AND RECOMMENDATIONS: Studies of at risk ethnic/racial groups and women with gestational diabetes are needed. Age and culturally sensitive programs need to be developed and evaluated. Studies of low-income diabetic women are required before determining potential interventions. Lifestyle programs in schools and workplaces are needed to promote well-being and combat obesity/inactivity, together with lobbying of the food industry for needed changes. High depression rates among diabetic women influence self-care ability and health care expenditures. Health professionals need further training in the use of effective counseling skills that will assist people with DM to make and maintain difficult behavioural changes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.007 |
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".