Bibliographic record
Abstract
Abstract Electric and magnetic fields (EMF) are ubiquitous. The earth has static electric fields, which produce lightning during thunderstorms, and geomagnetic fields created by electric currents within its core. Electric and magnetic fields are also produced during electric power generation, transmission, and use. Electric power has generally been considered safe during the more than 100 years of its use, although shocks and burns from direct contact with electrical conductors are a recognized health hazard. Of the approximately 1100 deaths from electric shock that occur each year in the United States, about three‐fourths result from unsafe operation of household appliances; accidents in the workplace account for the rest. The possible health consequences of electric and magnetic field exposure are a much more recent concern. Power‐frequency EMF exposure—unavoidable since the use of electricity has spread throughout the world—has been under investigation since the early 1970s. Investigations have included epidemiologic as well as in vitro and in vivo laboratory studies encompassing a wide range of diseases. The literature on EMF and health is vast, comprising over 1000 published studies, and has been reviewed in depth by several authoritative committees. Of note are reviews by the National Research Council of the National Academy of Sciences (NAS), the National Institute of Environmental Health Sciences (NIEHS) and the U.K. National Radiological Protection Board (NRPB). Electric power systems in the United States, Canada, and Mexico generate and transmit electricity as alternating current (ac), which oscillates at a frequency of 60 cycles per second, or 60 hertz (Hz). Most of the rest of the world generates power at 50Hz. Power‐frequency 50‐ and 60‐Hz fields occupy the extremely low‐frequency (ELF), nonionizing range of the electromagnetic spectrum. The ELF range includes frequencies from 3 to 3000Hz. Above 3000Hz are, in order of increasing frequency or decreasing wavelength, radio waves, microwaves, infrared radiation, visible light, ultraviolet radiation, x‐rays, and gamma rays. Microwaves have enough photon energy to heat tissue; ionizing radiation like x‐rays and gamma rays can damage biological systems by breaking chemical bonds. Extremely low‐frequency electric and magnetic fields can neither break bonds nor heat tissue, and the electric currents they induce in the body are very weak. Power‐frequency fields have very long wavelengths of about 5000km. Exposure distances are much shorter than this wavelength; under these circumstances, electric and magnetic fields are independent. Electric field strength increases with increasing voltage, or electric potential; magnetic field strength increases with increasing current. Both electric and magnetic fields decline rapidly with distance from their source, with a faster decline of fields from point sources such as machinery and a slower decline of fields from power lines. Electric fields are further reduced when shielded by conducting objects like buildings and have little penetrative ability; magnetic fields, on the other hand, are capable of penetrating tissue and are not easily shielded. Occupational exposure to electric and magnetic fields occurs from proximity to large motors as well as from wiring in buildings and the use of computers, office machines, and heating and air conditioning systems. Power transmission and distribution facilities are other sources. Accurate assessment of EMF exposure has presented many difficulties in epidemiologic studies and continues to be a considerable challenge. EMF have several unique characteristics that make them more difficult to measure than most other types of exposures. EMF are not readily detectable, are variable in time and space, and are to some extent present in all environments. Additionally, electric fields are both perturbed and intensified by conducting objects like the human body, so that fields measured at various points on the body's surface have different values. Because of the complexity of exposure circumstances, exposure reports from workers are not reliable.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".