Colorectal Cancer Screening in First Nations People Living in Manitoba
Bibliographic record
Abstract
BACKGROUND: Because the burden of colorectal cancer (CRC) seems to be increasing in First Nations, it is important to better understand CRC screening utilization. The objective of this study was to describe CRC screening among First Nations living in Manitoba. METHODS: The Federal Indian Register was linked to two provincial databases. A negative binomial model was used to compare the probability of First Nations having a fecal occult blood test (FOBT), colonoscopy, or flexible sigmoidoscopy (FS) with all other Manitobans. RESULTS: First Nations who lived in Winnipeg were significantly less likely to have had a FOBT in the previous 2 years than all other Manitobans who lived in Winnipeg [rate ratio (RR) = 0.40; 95% confidence intervals (CI), 0.37-0.44]. There was no difference in the likelihood of having a colonoscopy or FS for First Nations individuals who resided in northern Manitoba compared with all other Manitobans (RR, 1.04; 95% CI, 0.91-1.19). However, First Nations who lived in the rural south or urban areas were less likely than all other Manitobans to have had a colonoscopy or FS (RR, 0.81, 95% CI, 0.75-0.87, rural south; RR, 0.86, 95% CI, 0.81-0.92, urban). CONCLUSIONS: First Nations living in Winnipeg were significantly less likely to be screened for CRC using the FOBT. Colonoscopy and FS use depended on area of residence. IMPACT: First Nations experience barriers that impede the use of CRC screening. Further research is needed to understand these barriers to extend the benefit of CRC screening to this population. Cancer Epidemiol Biomarkers Prev; 24(1); 241-8. ©2014 AACR.
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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 | 0.002 |
| 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) | 0.002 | 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".