Mortality and cancer incidence in a cohort of registered nurses from British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: A retrospective cohort study of provincial registered nurses (RNs) from British Columbia, Canada was undertaken to determine risks of mortality and cancer incidence; in particular for breast cancer and leukemia. METHODS: Cohort records of RNs from 1974 to 2000 were linked to Canadian death and cancer registries. Analyses included standardized mortality (SMR) and incidence ratios (SIR) as well as relative risks for internal comparisons. RESULTS: There were 58,125 RNs in the cohort (96.7% females). The SMR for all causes of mortality for female RNs was low, at 0.61 (95% CI, 0.58-0.64). The only elevated SIR for female RNs was for malignant melanoma (1.27; 95% CI, 1.10-1.46). Ever working in a hospital, medical surgical specialties or maternal/pediatrics showed some elevated cancer risks. CONCLUSIONS: Low SMRs for the female RN cohort suggest healthful lifestyles and a healthy worker effect. Length of employment as a nurse, in hospitals and in specific fields was associated with some increased risks of cancer.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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 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".