Effects of Electromagnetic Fields on the Reproductive Success of American Kestrels
Bibliographic record
Abstract
Reduced reproductive success of birds nesting near power lines has been documented but never directly attributed to electromagnetic fields (EMFs). Laboratory studies have identified EMF effects on embryonic development, but reproductive success of wild birds is dependent on additional factors, including fertility, egg size, hatching, and fledging success. We tested whether EMFs affect reproductive success of birds. Captive American kestrels (Falco sparverius) were bred for one season per year for 2 yr under either controlled or EMF conditions. EMF exposure was equivalent to that experienced by wild reproducing kestrels and was weakly associated with reduced egg laying in 1 yr only. In both years fertility was higher, but hatching success was lower in EMF pairs than control pairs. Fledging success was higher in EMF pairs than control pairs in 1995 only. Egg composition and embryonic development were examined in 1 yr only, but hatchlings were measured in both years. EMF eggs were larger, with more yolk, albumen, and water, but had thinner egg shells than control eggs. Late-term EMF embryos were larger and longer than control embryos, although hatchlings were similar in body mass and size. EMF exposure affected reproductive success of kestrels, increasing fertility, egg size, embryonic development, and fledging success but reducing hatching success.
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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) | 0.000 | 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".