Longitudinal Changes in Prevalence of Colorectal Cancer in Farm and Non-Farm Residents of Saskatchewan
Bibliographic record
Abstract
OBJECTIVE: To determine predictors associated with longitudinal changes in colorectal cancer (CRC) prevalence in farm and non-farm rural residents in Saskatchewan, Canada. METHODS: Data from the Saskatchewan Rural Health Study were collected from 8261 individuals nested within 4624 households at baseline survey in 2010 and 4867 individuals (2797 households) at follow-up survey in 2014. The study sample consists of 5599 individuals (baseline) and 3933 at (follow-up) (more than or equal to 50 years). RESULTS: The prevalence of CRC increased over time among rural farm (baseline: 0.8%; follow-up: 1.3%, P < 0.05) and non-farm (baseline: 1.4%; follow-up: 2.0%, P > 0.05) residents. Longitudinal predictors of CRC prevalence were: quadrant, location of home, mother ever had cancer, age, body mass index (BMI), sex, radiation, natural gas. CONCLUSIONS: Longitudinal changes in prevalence of CRC among farm and non-farm residents appear to depend on a complex combination of individual and contextual factors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".