Seeking sanctuary: the neonatal calving period among central mountain woodland caribou (<i>Rangifer tarandus caribou</i>)
Bibliographic record
Abstract
Woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) populations have declined throughout their range. With the goal of better understanding habitat selection and fidelity during the neonatal calving period (0–4 weeks), we applied a noninvasive method that estimates calving events and subsequent survival based on changes in movement rates among GPS-collared female caribou. We examined a long-term GPS-collar data set (1998–2014) collected from 81 adult female caribou in two central mountain herds in Alberta and British Columbia, Canada. Although we were unable to validate our results with aerial surveys and pregnancy tests, our estimates of parturition rates, survival rates, calving dates, and habitat selection were consistent with previous studies. We identified 83 calving sites. Female caribou selected calving sites and postparturition habitat on high-elevation ridgetops with gradual slopes and avoided anthropogenic linear features. Female caribou displayed low fidelity to interannual calving ranges with a mean distance of 8.7 km between calving ranges. Fidelity was lower in areas with high seismic-line density. Conservation of high-elevation habitat with limited anthropogenic disturbance is likely to provide the greatest benefit to central mountain caribou during the neonatal calving period, and represents a potential management strategy for population recovery efforts.
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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 | 0.000 | 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".