Bibliographic record
Abstract
The Canadian Cancer Society says 139 900 new cases of cancer will be diagnosed in Canada in 2003, and 67 400 people will die from the disease. Males will account for approximately 51% of new cases and 53% of the deaths. Lung cancer alone is expected to cause 30% of cancer deaths in males this year (10 900), and 25% in females (7900). Breast cancer will kill 5300 women, while prostate cancer will claim 4200 men. For all cancers, the age-standardized mortality rate among men peaked in 1988 at 254.7 cases per 100 000 population, but it has now decreased to an expected rate of 223.7 cases per 100 000 in 2003. The age-standardized incidence rate increased slightly for males each year in the early 1990s, but then began to decline. In 2003, the age-standardized incidence rate is expected to be 439.2 per 100 000 for men, compared with 494.0 per 100 000 in 1993. For women, the incidence rate has risen from 330.0 cases per 100 000 in 1989 to an expected 347.9 in 2003. However, the mortality rate for females has declined since then, from 153.1 to an expected rate of 150.5 in 2003. — Tara S. Chauhan, 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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.074 | 0.028 |
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".