Elk (<i>Cervus elaphus</i>) railway mortality in Ontario
Bibliographic record
Abstract
Wildlife railway research is highly underrepresented in science despite documented wildlife–train collision mortalities. Gathering baseline information is imperative to the development of effective train collision mitigation, especially for at-risk or small reintroduced populations such as elk (Cervus elaphus Linnaeus, 1758) in eastern North America. We tested our hypotheses that elk–train collision rates vary in relation to railway structure and weather by using a combination of radiotelemetry and railway mortality surveys. Elk were closer to the railway in winter than in any other season. Elk–train collision sites were significantly closer to the apex of bends in the railway than random locations along the railway, and collision rates were positively related to snow depth. Railways may be perceived by elk as easy travel corridors, and deep snow likely prohibits escape from oncoming trains. This study gathered important information about an under-studied aspect of wildlife–human conflicts and provides a basis for the investigation of other species that may be affected by railways.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".