Factors Affecting Landscape Occupancy by Fishers in North‐Central British Columbia
Bibliographic record
Abstract
ABSTRACT To better understand distribution and density of fishers ( Martes pennanti ) in industrial forests of north‐central British Columbia, Canada, we examined factors affecting the probability of a potential home range being occupied by 10 radiotagged resident fishers in the Sub‐Boreal Spruce biogeoclimatic zone between 1996 and 2000. Percentage of a home range in wetlands and recently logged (within past 12 yr) best predicted likelihood of occupancy by each fisher. Probability of a home range area being occupied by a resident fisher decreased with increasing amounts of wetlands and recent logging present in the area. We estimated that a 5% increase in wetlands or recent logging decreased the relative probability of occupancy of a potential home range by 50%. The accelerated rate of timber harvest in forests affected by mountain pine beetle ( Dendroctonus ponderosae ) infestations may have substantial implications for the ability of the landscape of central British Columbia to support sustainable populations of fishers.
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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) | 0.002 | 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".