Habitat associations of American badgers in southeastern British Columbia
Bibliographic record
Abstract
Abstract: American badgers (Taxidea taxus) are endangered in British Columbia due to habitat loss and human-caused mortality. To better understand human impacts and to promote conservation planning, we described badger habitat rela-tionships. At two spatial scales, we analyzed selection by 12 radio-implanted resident badgers for soil composition, for-est overstory, land cover, vegetation productivity, terrain, and human influence. At a broad (23.8 km2) landscape scale, soil parent-material associations were positive with glaciolacustrine and glaciofluvial and negative with colluvial. Soil-order associations were positive with brunisols and regosols and negative with podzols and luvisols. Association with fine sandy-loam texture was positive. Associations were negative with forested habitats and positive with open range, agricultural habitats, and linear disturbances. Associations were negative with elevation, slope, terrain ruggedness, and both vegetation productivity and moisture. At a fine (14.5 ha) scale, associations were positive with glaciofluvial, fine sandy-loam textured, and well-drained soils. Associations were negative with colluvial soils, forest cover, vegetation moisture, elevation, and ruggedness. Associations with open range and southern aspects were positive. The linear com-bination of a subset of variables could explain and predict habitat selection. At this range extent, natural conditions may restrict badger occurrence, increasing badger sensitivity to human factors that influence habitat quality and mortality. Résumé: Les blaireaux d’Amérique (Taxidea taxus) sont menacés en Colombie-Britannique par la perte de leur habitat et la mortalité infligée par l’activité humaine. Pour mieux comprendre l’impact de l’activité humaine et pour encourager
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".