Movements and distribution of polar bears in the Beaufort Sea
Bibliographic record
Abstract
We fitted 173 satellite radio collars (platform transmitter terminals) to 121 adult female polar bears in the Beaufort Sea and relocated the bears 44 736 times between 1985 and 1995. We regularly resighted many instrumented bears so that we could ascertain whether changes in movements or distribution were related to reproductive status. Mean short-term movement rates were less than 2 km/h for all classes of bears. Maximum movement rates occurred in winter and early summer. In the southern Beaufort Sea (SBS), net geographic movements from the beginning to the end of each month were smaller for females with cubs of the year than for solitary females, and larger in November than in April, May, or July. In May, June, July, and August, radio-collared bears in the SBS moved north. They moved south in October. In the northern Beaufort Sea (NBS), bears moved north in June and south in March and September. Total annual movements ranged from 1406 to 6203 km. Mean total distances moved each month ranged from 79 to 420 km. Total monthly movements by SBS bears were largest in early winter and smallest in early spring. In the NBS, movements were largest in summer and smallest in winter. In the SBS, females with cubs moved less each month than other females. Annual activity areas ranged from 7264 to 596 800 km2. Monthly activity areas ranged from 88 to 9760 km2. Seasonal fidelity to activity areas of bears captured in all parts of the Beaufort Sea was strongest in summer and weakest in spring.
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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 | 0.000 |
| 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".