Premature Mortality Due to Malignancies of the Central Nervous System in Canada, 1980–2010
Bibliographic record
Abstract
BACKGROUND: In this study, we investigated whether there has been an improvement in premature mortality due to central nervous system (CNS) cancers among the Canadian population from 1980 through 2010. METHODS: Mortality data for CNS cancers were obtained from World Health Organization mortality database. Years of life lost (YLL) was estimated using Canadian life tables. Average lifespan shortened (ALSS) was calculated and defined as the ratio of YLL relative to the expected lifespan. RESULTS: Over this study period, we observed decreases in age standardized rates to the World Standard Population for mortality due to CNS cancers from 5.3 to 4.1 per 100,000 men, and from 3.6 to 2.9 per 100,000 women. Average YLL decreased from 23.6 to 21.5 years of life among men, and from 27.0 to 23.1 years among women in 1980 and 2010, respectively. The ALSS showed that men with CNS cancers lost 30.1% of their life span and women lost 32.5% in 1980, whereas they lost 25.8 and 26.6% in 2010, respectively. CONCLUSION: Our study shows that -Canadian people with CNS cancers have had their lives prolonged at the end of the study period.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".