Foreseeable Health Risk of Electric and Magnetic Field Residential Exposures
Bibliographic record
Abstract
Exposure to electric and magnetic fields (EMFs) emanating from the generation, distribution and utilization of electricity is widespread. The major debate in recent years has been the possibility that EMFs influence various effects on the human body especially development of cancer. Epidemiologists were the first scientists to publicize this fact through human population studies. Current investigations into this topic split up over diverse areas of research. This paper provides a review of information on health risk of EMF residential exposure. Four major areas have been considered for evaluating the possible risks with emphasis on recent studies. These include safety standards for EMFs, residential field measurement surveys, biological and epidemiological studies of diseases with foreseeable association with EMFs including childhood leukemia, breast cancer, and pregnancy adverse outcomes. On the basis of review findings, it is difficult to provide a robust conclusion about health risk of EMFs, raising the significance of researching this area further. No policy advise is offered, however, as a voluntary precautionary measure, public health professionals, regulatory authorities, standard setters, electric utilities, and individuals are encouraged to advocate minimizing EMF exposures wherever possible.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".