Winter Habitat Associations of a Low-Density Moose (<i>Alces americanus</i>) Population in Central Labrador
Bibliographic record
Abstract
Alces americanus (Moose) are relatively new to Labrador, having only colonized the area in the late 1940s, and little is known about this population. We conducted large-scale aerial surveys for Moose in a 122,000-km2 area during winter 2000 and in a 29,900-km2 area in winter 2001. Moose densities were low in each area (1.6–3.0 Moose per 100 km2). Bull:cow ratios were nearly even and calf:cow ratios were relatively high, indicative of a population exposed to little hunting or predation pressure. Twinning rates were low, suggesting low range productivity. Moose used riparian areas and hardwood stands in higher proportion than their availability in winter (P < 0.05). Open habitats (conifer-lichen woodlands, bogs and fens, burned forest, and barren areas) were used in lower proportion than their availability. These data may provide the basis for developing habitat suitability maps for Moose in late winter across central Labrador.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".