Wolverine, <em>Gulo gulo</em>, Home Range Size and Denning Habitat in Lowland Boreal Forest in Ontario
Bibliographic record
Abstract
We conducted the first radio-telemetry study of Wolverines in northwestern Ontario during the winter of 2003-2004 to determine whether home ranges and movements of Wolverines in lowland boreal forest were typical of this species in other ecosystems and to describe reproductive den sites in this habitat type. Seven Wolverines (3 M, 4 F) were radio-tagged and monitored for 31 to 269 (Mean ± SE = 153 ± 35) days using a combination of remotely monitored Argos satellite and conventional aerial telemetry. Male and female 95% minimum convex polygon (MCP) home ranges (±SE) during December to October were 2,563 (796) km2 and 428 (118) km2, respectively, for combined VHF and Argos locations. A lactating female had a 95% MCP home range of 262 km2. The den site for this female included large boulders and downed trees, similar to dens described for this species in montane ecosystems. Boulder complexes and downed trees may be critical features of wolverine dens in lowland boreal forests. Mean road densities (± SE) within 95% MCP and 50% MCP home ranges were 0.43 (0.13) and 0.33 (0.23) km/km2, respectively, and our results suggest that road densities may affect selection of home ranges by Wolverines. The Wolverine population was a resident, reproductive population. Erratum for table included.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".