Travel Rates of Wolves, <em>Canis lupus</em>, in Relation to Ungulate Kill Sites in Westcentral Alberta
Bibliographic record
Abstract
Recent advancements in Global Positioning Systems (GPS) radiocollar technology permit analysis of fine-scale animal movements. We used concurrent aerial and GPS monitoring to determine winter travel rates of Wolves (Canis lupus) in relation to ungulate kill sites in managed forest landscapes in westcentral Alberta. Wolves preyed predominately on Moose (Alces alces) and travelled 4.2 times less when near ungulate kill sites than when away from them. As Wolves are thought to be an important factor in Woodland Caribou (Rangifer tarandus caribou) declines, information is needed to assess predation risk to Caribou from Wolves under a variety of landscape conditions. If Wolves have restricted movements near Moose kill sites, this may lead to decreased encounter rates with Caribou in systems where Moose are abundant. Deer (Odocoileus spp.) are probably an important component of this Wolf-prey system but little is currently known about this relationship. Projecting long-term implications of ongoing development activities requires a more detailed understanding of the responses of all species to landscape change.
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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 | 0.001 | 0.001 |
| 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".