Winter movement behavior by swift foxes (<i>Vulpes velox</i>) at the northern edge of their range
Bibliographic record
Abstract
Winter can be a limiting time of year for many temperate species, who must access depressed prey resources to meet energetic demands. The swift fox (Vulpes velox (Say, 1823)) was extirpated from Canada and Montana (USA) by 1969, but was reintroduced in the 1980s to Canada, and subsequently spread into northern Montana. Swift foxes in this region are at the current northern range edge where winter conditions are harsher and persist longer than in their southern range (i.e., Colorado (USA) to Texas (USA)). We collected fine-scale locational data from swift foxes fitted with global positioning system collars to examine movement and resource-use patterns during winter of 2016–2017 in northeastern Montana. Our results suggest that swift foxes displayed three distinct movement patterns (i.e., resting, foraging, and travelling) during the winter. Distance to road decreased relative probability of use by 39%–46% per kilometre across all movement states and individuals, whereas the influence of topographic roughness and distance to crop field varied among movement states and individuals. Overall, while our findings are based on data from three individuals, our study suggests that across movement states during the critical winter season, swift foxes are likely using topography and areas near roads to increase their ability to detect predators.
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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 | 0.000 | 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".