Conservation of Grizzly Bear populations and habitat in the northern Great Bear Rainforest
Bibliographic record
Abstract
Abstract There are now at least eleven “threatened” Grizzly population “units” in British Columbia and one quarter of the province is now either without Grizzlies (8%) or occupied by threatened populations (16%). B.C. Grizzly populations are moving toward extinction in more than 25% of the province, an increase in area of more than 200% since 1965. This paper evaluates the Protected Areas (PAs) proposed for the North Coast Plan in the context of published understanding of Grizzly Bear ecology, behavior and movements, population densities, and effective population size. It also investigates the relationship between commercially productive forest and the designation of PAs as well as compares conservation strategies in Alaska's Tongass National Forest (Habitat Conservation Areas, HCAs) and BC's North Coast Plan area PAs. The conservation biology analysis reveals that this North Coast plan is dangerously inadequate and recommendations are made for an additional 3 large and 19 medium-sized PAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".