Effect of Electric and Magnetic Fields (60 Hz) on Production, and Levels of Growth Hormone and Insulin-Like Growth Factor 1, in Lactating, Pregnant Cows Subjected to Short Days
Bibliographic record
Abstract
Electric and magnetic fields (EMF) are generated by the transmission of electricity through high tension lines traversing rural areas. Previous studies showed increased dry matter intake (DMI) and fat corrected milk in dairy cows exposed to EMF. Because EMF exposure has been shown to suppress pineal release of melatonin in some species, it was hypothesized that EMF effects resemble those of exposure to long days. Previous studies have shown that DMI and milk production increase in dairy cattle in response to long day photoperiods, and this has been observed in association with increased circulating insulin-like growth factor 1 (IGF-1), but not growth hormone (GH). The hypothesis that EMF act by modifying the response to photoperiod was tested by subjecting dairy cows to controlled EMF exposure while keeping them under short-day conditions. Sixteen lactating, pregnant Holstein cows were exposed to a vertical electric field of 10 kV/m and a horizontal magnetic field of 30 microT in a crossover design with treatment switchback. Two groups of eight cows each were exposed to EMF for 16 h/d in either oftwo sequences. Each sequence consisted of three consecutive 28-d periods. All animals were maintained under short day conditions (8 h light, 16 h dark) during the trial. DMI and plasma IGF-1 were increased (P < 0.01) during EMF exposure (17.03 vs.16.04 kg/d, SE = 0.4; 137 +/- 6 ng/ml vs 126 +/- 6, respectively). The mean GH concentration was not affected, but a treatment x hour interaction was detected, with GH lower for the EMF exposed animals during the first 16 h of the sampling period, and higher for the last 8 h. Overall, the yield of milk or its components was not affected by EMF exposure, but milk yield was significantly higher for the exposed animals during wk 4 of treatment.
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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 | 0.000 |
| 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 | 0.000 | 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 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".