SPATIAL SEPARATION OF CARIBOU FROM MOOSE AND ITS RELATION TO PREDATION BY WOLVES
Bibliographic record
Abstract
In northeastern Alberta, Canada, continued expansion of the oil and gas industry along with timber harvesting has raised concerns that the resulting environmental changes may negatively affect the woodland caribou (Rangifer tarandus caribou) population in this region. Caribou are a threatened species in Alberta, and populations in northeastern Alberta appear to be stable or slightly decreasing. The spatial distribution of caribou in relation to alternative prey (commonly moose [Alces alces]) has been hypothesized to affect the level of wolf (Canis lupus) predation on caribou populations. We monitored radiomarked caribou, moose, and wolves between 1993 and 1997, and we found that selection of fen/bog complexes by caribou and selection of well-drained habitats by moose and wolves resulted in spatial separation. This spatial separation in turn reduced wolf predation pressure on caribou but did not provide a total refuge from wolves. Any management activities that increase the density of moose and wolves or increase access of wolves into fen/bog complexes will likely reduce the refuge effect provided by large fen/bog complexes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".