Gray Wolves, Canis lupus, of British Columbia's Central and North Coast: Distribution and Conservation Assessment
Bibliographic record
Abstract
The Gray Wolves (Canis lupus) of coastal British Columbia are a remnant group of a much larger population that once inhabited most of North America, including its west coast temperate rainforests. During summers 2000 and 2001, we surveyed 36 islands and 42 mainland watersheds on British Columbia's Central and North Coast for the presence of wolves. An extensive survey had not been conducted previously. We observed wolf sign at all locations, including islands or island groups separated by approximately 7, 8, and 12-km from other large landmasses. The distribution of wolves on islands may be dynamic, with occupancy by solitary Wolves or packs being ephemeral. The potential for an island to support a persistent population of wolves may depend on the presence and abundance of their main prey, Black-tailed Deer (Odocoileus hemionus), and security from exploitation by humans. These factors likely are mediated by island isolation, area, shape, topography, and extent of logging. Mounting evidence suggests that logging negatively affects Wolves in temperate rainforests by reducing carrying capacity for deer.
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 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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".