Blood melatonin and prolactin concentrations in dairy cows exposed to 60 Hz electric and magnetic fields during 8 h photoperiods
Bibliographic record
Abstract
Two experiments were conducted to test the hypothesis that electric and magnetic field (EMF) exposure may result in endocrine responses similar to those observed in animals exposed to long days. In the first experiment, 16 lactating, pregnant Holstein cows were assigned to two replicates according to a crossover design with treatment switchback. All animals were confined to wooden metabolic cages and maintained under short day photoperiods (8 h light/16 h dark). Treated animals were exposed to a vertical electric field of 10 kV/m and a horizontal magnetic field of 30 microT (EMF) for 16 h/day for 4 weeks. In a second, similar experiment, 16 nonlactating, nonpregnant Holstein cows subjected to short days were exposed to EMF, using a similar protocol, for periods corresponding to the duration of one estrous cycle. In the first experiment, circulating MLT concentrations during the light period showed a small numerical decrease during EMF exposure (P < .05). Least-square means for the 8 h light period were 9.9 versus 12.4 pg/ml, SE = 1.3. Melatonin concentrations during the dark period were not affected by the treatment. A similar trend was observed in the second experiment, where MLT concentrations during the light period tended to be lower (8.8 pg/ml vs. 16.3 pg/ml, P < .06) in the EMF exposed group, and no effects were observed during the dark period. Plasma prolactin (PRL) was increased in the EMF exposed group (16.6 vs. 12.7 ng/ml, P < .02) in the first experiment. In the second experiment, the overall PRL concentrations found were lower, and the mean plasma PRL concentration was not affected by treatment. These experiments provide evidence that EMF exposure may modify the response of dairy cows to photoperiod.
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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".