O-181 Occupational exposure to extremely low-frequency magnetic fields and postmenopausal breast cancer risk
Bibliographic record
Abstract
Introduction The International Agency for Research on Cancer has classified Extremely Low-Frequency Magnetic Fields (ELF-MF) as possibly carcinogenic to humans but the literature on occupational exposure to ELF-MF and breast cancer risk is sparse. Material and Methods In this population-based case-control study, incident cases of histologically confirmed postmenopausal breast cancer were identified at 18 hospitals in Montreal, Canada, 2008–2011. Population controls comprised women without a history of breast cancer, randomly selected from the electoral list for Montreal, and frequency-matched to cases using 5-year age groups. We elicited information on occupational history and potential risk factors. An occupational hygienist coded all jobs to the International Standard Classification of Occupations 1988 (ISCO88); these occupation codes were linked to an ELF-MF job exposure matrix (JEM) to obtain mean workday-average ELF-MF exposure. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for incident breast cancer and past ELF-MF cumulative exposure (CE) and average exposure (AE), adjusting for individual-level and ecological covariates. Separate analyses were conducted restricting exposure before the first full-term pregnancy or age 35 for women who were never pregnant and for hormonal receptor phenotypes. Results We recruited 592 controls and 663 cases. The fully adjusted ORs per increase in the interquartile range (IQR=2.12 μT-years) of CE was 0.99 (95% CI: 0.94–1.06) and for AE (IQR=1.54 μT) was 0.96 (95% CI: 0.90–1.02). The associations between breast cancer and ELF-MF CE and AE were consistent with linearity. Adjustments for various combinations of potential confounders did not change these patterns. We found no evidence of associations for different breast cancer subtypes or exposure before the first full-term pregnancy or the age of 35. Conclusions Our findings suggest that occupational exposure to ELF-MF, assigned here using a JEM, may not be associated with the risk of incident postmenopausal breast cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".