Estimating raptor electrocution mortality on distribution power lines in Alberta, Canada
Bibliographic record
Abstract
ABSTRACT Raptor electrocution mortality on power lines has been well documented over the past several decades, yet knowledge gaps, particularly regarding electrocution rates and estimates of losses, are still prevalent in the literature. Mortality estimates that do exist are often derived solely from utility outage records and exclude those not associated with a sustained outage. To address these shortcomings, we directly assessed raptor electrocution mortality beneath distribution power lines in east‐central Alberta, Canada between June and August 2003. We also experimentally tested the effect of scavenger removal of carcasses. We observed the greatest rate of raptor mortality on transformer poles; 3‐phase corner deadend poles were implicated in more incidents than expected based on proportional frequency, whereas tangent structures showed the opposite result. An estimated 94% of electrocution mortality was not associated with a power outage, indicating that utility outage data alone is insufficient to estimate incidence of electrocution. Scavenger removal rates were high, with >50% of the experimental carcasses removed within 7 days. Study results will assist utility companies and wildlife managers to better delineate structure retrofitting and new construction standards for structures that cause a disproportionately high number of raptor electrocutions, maximizing limited mitigation funds. © 2013 The Wildlife Society.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".