A review of screening mammography participation and utilization in Canada
Bibliographic record
Abstract
INTRODUCTION: Participation rate is an important indicator for a screening program's effectiveness; however, the current approach to measuring participation rate in Canada is not comparable with other countries. The objective of this study is to review the measurement of screening mammography participation in Canada, make international comparisons, and propose alternative methods. METHODS: Canadian breast cancer screening program data for women aged 50 to 69 years screened between 2004 and 2006 were extracted from the Canadian Breast Cancer Screening Database (CBCSD). The fee-for-services (FSS) mammography data (opportunistic screening mammography) were obtained from the provincial ministries of health. Both screening mammography program participation and utilization were examined over 24 and 30 months. RESULTS: Canada's screening participation rate increases from 39.4% for a 24-month cut-off to 43.6% for a 30-month cut-off. The 24-month mammography utilization rate is 63.1% in Canada, and the 30-month utilization rate is 70.4%. CONCLUSION: Due to the differences in health service delivery among Canadian provinces, both programmatic participation and overall utilization of mammography at 24 months and 30 months should be monitored.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.017 | 0.031 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".