Wolverine, <em>Gulo gulo luscus</em>, Resting Sites and Caching Behavior in the Boreal Forest
Bibliographic record
Abstract
Wolverine (Gulo gulo luscus) caches and resting sites were examined in a study area in the boreal upland forests of northwestern Alberta and northeastern British Columbia (approximately 57°N). Cache sites were in climax, or “overmature” stands of Black Spruce (Picea mariana) or mixed-wood of high complexity, dominated by conifers, and in which the Trembling Aspen (Populus tremuloides) and Balsam Poplar (Populus balsamifera) component consisted of mostly dead or dying trees characteristic of such old growth in the boreal uplands. Sites offered relatively good visibility of the surrounding stand. Sites were never located in the dense to extremely dense homogenous spruce stands documented as being favored for travel by Wolverines in the study area. The better used cache complexes were accessed by numerous well-used trails made by the Wolverines themselves. Caches consisted of the bones, hide and hair of Moose (Alces alces) believed to have been killed by Grey Wolves (Canis lupus). Caches were classified as “simple caches” composed of a single feeding site and/or excavation and “cache complexes” involving one or more feeding “stations”, latrines, resting sites, and climbing trees that may have been used as avenues of escape from competitors/predators. Resting sites were located atop the snow in relatively open locations that offered good visibility of the surroundings. Climax stands were implicated as being of importance to Wolverine caching behavior. Conservation implications include the detrimental effect on Wolverine populations likely to result from current timber harvesting practices in the boreal forest.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".