Maternal den site fidelity of polar bears in western Hudson Bay
Bibliographic record
Abstract
Abstract Seasonal migrations allow to access temporally varying resources and individuals may show fidelity to specific locations. Polar bears ( Ursus maritimus ) are a sea ice dependent species that migrate between marine and terrestrial habitats, the latter being important for parturition and early cub rearing. However, fidelity to maternity den sites is poorly understood. We assessed polar bear maternal den site fidelity of the Western Hudson Bay subpopulation in Manitoba, Canada. Using capture and telemetry data collected between 1979 − 2018, we examined site fidelity from 188 maternity den locations from 78 individuals. We calculated within-individual inter-year distances between dens, and compared these to between-individual distances via non-parametric bootstrapping. We used generalised additive models to assess how maternal age, years between denning events, and sea ice conditions affected site fidelity. We found some evidence of site fidelity, as within-individual inter-year distances were smaller than between-individual den distances by approximately 18.5 km. As time between captures increased, inter-den distances also increased (ranging from approximately 25 km to 55 km), but no other variables significantly affected fidelity. Our findings suggest that western Hudson Bay polar bears show a moderate amount of fidelity to denning areas, but not necessarily to specific sites.
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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 | 0.001 |
| 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) | 0.001 | 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".