Occupational exposures to extremely low frequency magnetic fields and postmenopausal breast cancer
Bibliographic record
Abstract
BACKGROUND: The association between occupational exposure to extremely low frequency magnetic fields (ELF-MF) and risk of postmenopausal breast cancer was assessed in a case-control study. METHODS: Breast cancer cases were compared to cancer controls. Interviewers elicited information on risk factors and on lifetime work history. Industrial hygienists assigned to each job average duration of exposure to ELF-MF at four levels of intensities ("none," <0.2 microT; "low," 0.2-<0.5microT; "medium," 0.5-<1microT; "high," > or =1-10microT). Unconditional logistic regression was used to estimate adjusted odds ratios (OR) and 95% confidence intervals (95% CI). RESULTS: A total number of 608 cases and 667 controls participated. Adjusting for accepted breast cancer risk factors, we found an OR of 1.13 for lifetime occupational exposure to ELF-MF at medium or high intensities. Risks were larger for exposures before age 35 (OR = 1.40), and statistically significant for exposures before 35 among cases with progesterone receptor positive tumors (OR = 1.56, 95% CI=1.02-2.39). CONCLUSIONS: There appears to be a small increased risk for breast cancer among postmenopausal women exposed occupationally to ELF-MF.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".