Projection of future cancer incidence and new cancer cases in Manitoba, 2006–2025
Bibliographic record
Abstract
INTRODUCTION: Projecting the burden of cancer is important for evaluating prevention strategies and for administrative planning at cancer facilities. METHODS: We projected cancer incidence and counts for the population of Manitoba using population projections from the Manitoba Bureau of Statistics for the years 2006 to 2025 and cancer incidence data from the Manitoba Cancer Registry for the years 1976 to 2005. Data were analyzed using a version of the age-period-cohort model with recommended modifications that was developed and tested in the Nordic countries. RESULTS: The overall incidence of cancer in Manitoba is not projected to change substantially from 2006 to 2025. However, the age-standardized incidence for lung cancer is expected to decrease, particularly for males, highlighting the importance of tobacco prevention. The total number of new cancer cases per year is expected to increase 36% over the projection period, attributable primarily to demographic changes. CONCLUSION: As the population of Manitoba increases, resource and infrastructure planning will need to account for the expected increase in cancer cases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".