Bibliographic record
Abstract
The Canadian Cancer Society estimates that 65 300 Canadians died from cancer in 2001 and another 134 100 developed the disease. Men developed it at a slightly higher rate than women (4.47 cases per 1000 population versus 4.17 per 1000). The death rate was also higher for men, 2.25 per 1000 compared with 1.96 per 1000. The deaths-to-cases ratio, a crude measure of disease severity, was slightly lower for women (0.47:1) than men (0.50:1). In 2001, gender-specific cancers (breast and prostate) accounted for 28% of new cases and 15% of deaths. Lung cancer represented 16% of new cases, while colorectal cancer accounted for 13%. In the last decade, age-standardized incidence rates decreased for men but increased for women. In 1991 the incidence rate for men was 469.0 cases per 100 000. It peaked at 493.5 cases in 1993 and decreased to 444.5 cases in 2001. For women, the incidence rate rose from 337.1 cases per 100 000 in 1991 to 343.9 per 100 000 in 2001. The incidence rates for both breast and prostate cancer have increased since 1991, as have both male and female rates for colorectal cancer. The lung cancer incidence rate for males decreased from 90.7 to 77.3 per 100 000 during the last 10 years, but the rate for females has moved in the other direction, increasing to 47.4 cases per 100 000 women from 37.7 cases. — Shelley Martin, Senior Analyst, Research, Policy and Planning Directorate, CMA
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.044 | 0.018 |
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".