Progress in cancer control leads to a substantial number of cancer deaths avoided in Canada
Bibliographic record
Abstract
It is currently not known how many more cancer deaths would have occurred among Canadians if cancer mortality rates were unchanged following various modern human interventions. The objective of this study was to estimate the number of cancer deaths that have been avoided in Canada since the age-standardized overall cancer mortality rate peaked in 1988. We applied the age-specific overall cancer mortality rates from 1988 to the Canadian population for all subsequent years to estimate the number of expected deaths. Avoided cancer deaths were estimated as the difference between the observed and expected number of cancer deaths for each year. Since 1988, there have been 372 584 (standardized mortality ratio = 0.77) and 120 045 (standardized mortality ratio = 0.90) avoided cancer deaths in males and females, respectively (492 629 total). Nearly half a million cancer deaths have been avoided in Canada since the overall cancer mortality rate peaked, which demonstrates the exceptional progress made in modern cancer control in Canada.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.001 | 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".