Canadian Radiologists Do Not Support Screening Mammography Guidelines of the Canadian Task Force on Preventive Health Care
Bibliographic record
Abstract
PURPOSE: The study sought to determine screening mammography recommendations that radiologists in Canada promote to average-risk patients and family or friends, and do or would do for themselves. METHODS: An online survey was delivered from February 19, 2014, to July 11, 2014. Data included radiologists' recommendations for mammography and their personal screening habits based on gender. The 3 radiologists' cohorts were women ≥40 years of age, women <40 years of age, and men. The distribution of responses for each question was summarized, and proportions for the entire group and individual cohorts were computed. RESULTS: Of 402 surveys collected, 97% (299 of 309) radiologists recommended screening every 1-2 years, 62% (192 of 309) starting ≥40 years of age and 2% (5 of 309) recommended screening every 2-3 years for women 50-74 years of age. Recommendations were similar for family and friends: 96% (294 of 305) recommended screening every 1-2 years, 66% (202 of 305) recommended screening every 1-2 years for women ≥40 years of age, and 2% (5 of 305) recommended screening every 2-3 years. For women radiologists ≥40 years of age, 76% (48 of 63) underwent screening every 1-2 years and started at 40 years of age, 76% (16 of 21) female radiologists <40 years of age would undergo screening ≥40 years of age, 100% every 1-2 years, and 90% (151 of 167) male radiologists would undergo screening every 1-2 years, with 71% (120 of 169) beginning at 40 years of age. CONCLUSION: The majority of Canadian radiologists recommend screening mammography every 1-2 years for average-risk women ≥40 years of age, whether they are patients or family and friends.
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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 | 0.015 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".