The Effects of Electromagnetic Fields From Power Lines on Avian Reproductive Biology and Physiology: A Review
Bibliographic record
Abstract
Electrical power lines are ubiquitous in the developed world and in urban areas of the developing world. All electrical currents, including those running through power lines, generate electric and magnetic fields (EMFs). Electrical power lines, towers,and distribution poles are used by birds for perching, hunting, and nesting. Therefore, many bird species, like humans, are exposed to EMFs throughout their lives. EMFs have been implicated in adversely affecting multiple facets of human health,including increasing the risks of life-threatening illnesses such as leukemia, brain cancer, amyotrophic lateral sclerosis, clinical depression, suicide, and Alzheimer's disease. A great deal of research and controversy exists as to whether or not exposure to EMFs affects the cellular, endocrine, immune, and reproductive systems of vertebrates. Laboratory work has used mice, rats, and chickens as models for this EMF research in an effort to understand better the possible implications of EMF exposure for humans. However, EMF exposure of wild birds may also provide insight into the impacts of EMFs on human health. This review focuses on research examining the effects of EMFs on birds; most studies indicate that EMF exposure of birds generally changes, but not always consistently in effect or in direction, their behavior, reproductive success, growth and development, physiology and endocrinology, and oxidative stress under EMF conditions. Some of this work has involved birds under aviary conditions, while other research has focused on free-ranging birds exposed to EMFs. Finally, a number of future research directions are discussed that may help to provide a better understanding of EMF effects on vertebrate health and conservation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".