A program to monitor moose populations in the Dehcho Region, Northwest Territories, Canada.
Bibliographic record
Abstract
Moose (Alces alces) are an important traditional and spiritual resource for residents of the Dehcho Region of the Northwest Territories. Maintaining healthy and sustainable populations of moose for future generations is a goal of the Department of Environment and Natural Resources (ENR). Following a regional wildlife workshop with Dehcho First Nations, the need for a program to determine baseline information on moose populations and to foster community-based monitoring of moose in the Dehcho was identified. Such a program needed to be established prior to future proposed developments including the Mackenzie Gas Project. After extensive community consultation between local First Nations and ENR, a baseline aerial survey over a large area of the Dehcho was designed, and was to be followed by an annual monitoring program. Two key components identified for the annual monitoring program were an aerial survey and harvest sampling. The aerial survey would provide information on moose density and calf production, and harvest sampling would provide information on the relative health and physical condition of animals consumed by local residents. In light of increasing developmental pressures in the region, such information collected over time is important to harvesters, First Nations, wildlife managers, and land use planners alike because it should document change in the quantity and quality of a key traditional wildlife resource. Population estimates from the aerial surveys indicated that the estimated population density and calf:cow ratios were reasonable. Harvest data indicated low incidence of diseases and parasites, low levels of cadmium in organ tissue, and that moose were mostly in good or excellent body condition based on observation and fat indices. This study is an example of successfully combining the knowledge and cooperation of First Nation moose harvesters with the technical support of government biologists to secure valuable biological information for baseline data to monitor change associated with development in a region.
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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 | 0.001 | 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 | 0.002 | 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".