Rocky Mountain bighorn sheep (<i>Ovis canadensis canadensis</i>) winter habitat selection and seasonal movements in an area of active coal mining
Bibliographic record
Abstract
Winter is an important period for most mountain ungulates due to limited availability of preferred forage and costs associated with travel through deep snow. We examined winter habitat selection by Rocky Mountain bighorn sheep (Ovis canadensis canadensis Shaw, 1804) where four large, open-pit coal mines are in operation. Sheep in this area generally winter at high elevation on windswept, south-facing native grasslands. We used GPS collars and Resource Selection Function analysis to examine movements and habitat selection. A majority (79%) of the sheep were migratory and fidelity to winter ranges was high (88%). Sheep showed low use (∼10%–20%) of mine areas between November and April, followed by increased use peaking at 60%–65% in September–October. Wintering sheep were positively associated with high elevations, closeness to escape terrain, and warmer aspects. High-elevation, native grasslands were the highest ranked cover class. Most sheep that used mine areas during winter used reclaimed habitats, primarily reclaimed spoils and pits. Primary winter ranges comprised 4.3% of merged sheep range, emphasizing the limited amount of occupied winter ranges within the landscape. Disturbance to native winter range resulting from development should be minimized or be conducted in a manner that effectively manages and (or) mitigates the impacts.
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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 | 0.000 |
| 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) | 0.001 | 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".