Distribution of subadult grizzly bears in relation to human development in the Bow River Watershed, Alberta
Bibliographic record
Abstract
We studied the relationship between human development and activity, and subadult grizzly bears (Ursus arctos) by comparing the distribution of radiotelemetry locations from 23 subadult versus 29 adult grizzly bears during 1994–2000 in the Bow River Watershed of Alberta, Canada. We used logistic regression to model significant differences in the spatial distribution of subadult and adult grizzly bears and analysis of variance (ANOVA) to test for significant differences in temporal distribution. Subadult bears were significantly closer to high-use roads and at lower elevations than adult bears. Both subadult and adult bears were significantly closer to high-use roads and at lower elevations during human inactive periods (1800–0700) than during human active periods (0700–1800). Subadult bears were closer to high-use roads regardless of the time of day, and therefore predisposed to greater encounter rates with humans. Consequently, subadult bears had a greater chance of becoming habituated to humans and of being killed or removed from the population by humans than adult bears. In areas with high levels of human use, we recommend that grizzly bear managers consider the population effects of these losses.
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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 | 0.001 | 0.001 |
| 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".