What factors predict path tortuosity of Great Basin pocket mice in shrub-steppe habitat invaded by cheatgrass?
Bibliographic record
Abstract
Abstract Foraging animals choose habitats based on characteristics that often cannot be satisfied simultaneously, such as easy mobility, abundant or high-quality foods, and safety from predators. Invasive plants may alter habitat structure and provide novel foods; thus, measuring how animals forage in invaded landscapes offers insights into these new ecological relationships. We examined the movements of Great Basin pocket mice (Perognathus parvus) in sage-steppe habitats invaded by cheatgreass (Bromus tectorum) in southcentral British Columbia, Canada. The pathway tortuosity (fractal D) of pocket mice increased with vegetative cover and population density and decreased with open habitat, but these variables explained little of the variation in tortuosity. The fractal dimension of movement pathways of pocket mice was consistent over spatial scales ranging from 0.5 m to two-thirds of the home range size, unlike in other species where fractal dimensions are not consistent over multiple spatial scales. Collectively, our results indicate that foraging movements of pocket mice were not affected by the low densities of cheatgrass in this system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".