Ecological and physiological factors influencing the use of mineral licks by Stone’s sheep ( <i>Ovis dalli stonei</i> )
Bibliographic record
Abstract
Access to trace minerals is essential to the physiological functions of ruminant species. Deficiency in essential minerals can cause adverse effects ranging from reduced growth to impaired metabolic function and fitness to mortality of adults and neonates. Ungulates commonly practice geophagia at areas referred to as “licks”, where they obtain minerals presumably lacking in their diet. We used local knowledge and Global Positioning System collar data from 19 Stone’s sheep ( Ovis dalli stonei J.A. Allen, 1897) in the Cassiar Mountains of northwestern British Columbia, Canada, to locate mineral licks. We used the location data from 18 collared female sheep and fractional regression to test 13 model hypotheses that explained the frequency and timing of visitation to five licks. Hypotheses represented the physiological traits of collared sheep, site elevation, vegetation, adjacency of human disturbance, and mineral composition of the soil at the lick. We found that visitation was best described by models that included nursing status of ewes, concentration of magnesium and sodium in the soils, and the elevation of the mineral lick. These findings supported our prediction that post-parturient ewes would use mineral licks at a greater rate than ewes without lambs. Location data for one Stone’s sheep ram were analyzed, and this individual spent a greater proportion of his time at licks than all ewes in the study. Our results suggest that mineral licks are an important habitat feature for Stone’s sheep.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".