Bibliographic record
Abstract
Native grasslands are home to a disproportionate share of species at risk, and typically consist of a mosaic of ranchland and protected parkland. Livestock carcasses can attract coyotes and potentially subsidize the coyote population or increase depredation, which is a concern to ranchers in southwest Saskatchewan. A subsidized predator population may increase pressure on native prey species through apparent competition. In this thesis, I investigated the relationship between coyotes, cattle and native prey. In the second chapter, I used molecular methods to test how commonly coyotes consumed cattle and species at risk, and how geographic factors affected the presence of cattle versus deer in coyote diet. Deer and cattle were the most common food items. Scat containing cattle was typically found closer to a boneyard and the bison enclosure, whereas scat containing deer was typically further from a boneyard and the bison enclosure. Different individual coyotes may be consuming cattle versus deer and coyotes consuming cattle may show different travel behaviour than coyotes consuming native prey. However, I found no evidence that coyotes pose a direct threat to species at risk during the winter. In the third chapter, I observed coyotes during summer to test whether coyotes obtained direct and/or indirect benefits from cattle pastures, and how cows responded to the presence of coyotes. Coyotes hunted native prey and specifically ground squirrels more commonly than cattle, showing that they obtained indirect benefits from the use of cattle pastures. Cows responded to coyotes defensively, and although observations of coyotes approaching individual calves, rushing cow-calf herds, or harassing females for afterbirth were uncommon, these observations, combined with the coyotes’ scavenging from cattle carcasses, indicate that coyotes also benefit directly by consuming cattle or cattle by-products. Further work identifying individual coyotes would help to determine what proportion of the population is being subsidized by cattle and factors that might predispose individual coyotes to depredation.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".