Evidence for historical grizzly bear occurrence in the North Cascades, USA
Bibliographic record
Abstract
The North Cascades ecosystem of north-central Washington State (USA) and southern British Columbia, Canada, has been identified as 1 of 6 recovery zones for grizzly bears (Ursus arctos) that were at one time distributed across a nearly continuous range of western North America. The current small number of grizzly bears, along with an apparent scarcity of historical observations, obfuscates the extent to which the mountain range and its surrounding lowlands previously supported grizzly bears. We reviewed and synthesized what is currently known about the historical distribution of grizzly bears in and around the North Cascades to better inform possible future restoration actions. Archeological, ethnographic, and incidental evidence confirm the prehistoric and historic presence of grizzly bears in the ecosystem and surrounding lowlands. Successful implementation of grizzly bear restoration and management in the North Cascades is dependent in part on the perception that they are an integral component of the ecosystem's historical benchmark. Education and outreach efforts that focus on the influence of human perceptions and correcting misinformation about the history of bears in the ecosystem and their interactions with humans may improve long-term restoration success in the North Cascades.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".