Distribution of barren‐ground caribou during winter in response to fire
Bibliographic record
Abstract
We investigated the influence of past fires on the large‐scale distribution of barren‐ground caribou (Rangifer tarandus groenlandicus) in the Northwest Territories, Canada, during winter. We used an information‐theoretic approach and data describing fire history, vegetation, and predation risk to develop resource selection functions that explained caribou distribution on early‐ and late‐winter ranges. We evaluated multiple sets of models constructed across years for all caribou (pooled models) and for individual caribou by period (early and late winter). Winter range habitats important to caribou were characterized by a high percentage of ground cover of lichen and herbaceous forage and a close proximity to lakes and rivers. Although caribou avoided areas densely populated with burns, there was considerable use of early‐seral habitats as well as areas adjacent to the burn boundary. Disparate selection strategies among caribou highlight the importance of investigating both individual and global resource selection models. These results suggest that at some spatial and temporal scales, individual barren‐ground caribou may be less averse to fire than previously thought.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".