Printed in U.S.A Leukemia following Occupational Exposure to
Bibliographic record
Abstract
In a nested case-control study of 1,484 cancer cases and 2,179 matched controls from a cohort of 31,543 Ontario Hydro male employees, the authors evaluated associations of cancer risk with electric field exposure and reevaluated the previously reported findings for magnetic fields. Pensioners were followed from January 1, 1970, and active workers (including those who left the corporation) from January 1,1973, with both groups followed through December 31,1988. Exposures to electric and magnetic fields and to potential occupational confounders were estimated through job exposure matrices. Odds ratios were elevated for hematopoietic malignancies with cumulative electric field exposure. After adjustment, the odds ratio for leukemia in the upper tertile was 4.45 (95 % confidence interval (Cl) 1.01-19.7). Odds ratios were also elevated for acute nonlymphoid leukemia, acute myeloid leukemia, and chronic lymphoid leukemia. For cumulative magnetic field exposure, there were similar elevations that fell with adjustment. Evaluation of the combined effect of electric and magnetic fields for leukemia showed significant elevations of risk for high exposure to both, with a dose-response relation for increasing exposure to electric fields and an inconsistent effect for magnetic fields. There was some evidence of a nonsignificant association for brain cancer and benign brain tumors with magnetic fields. For lung cancer, the odds ratio for high exposure to electric and magnetic fields was 1.84 (95 % Cl 0.69-4.94). Am J Epidemiol 1996; 144:150-60.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.239 | 0.066 |
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".