Seasonal and annual movement patterns of polar bears on the sea ice of Hudson Bay
Bibliographic record
Abstract
Polar bears ( Ursus maritimus Phipps, 1774) move thousands of kilometres over sea ice searching for mates and hunting for seals, which are their primary prey. Recently, decreased sea ice extent and earlier ice break-up have been linked to shifts in seal distribution and abundance and to declines in polar bear condition and numbers in the western Hudson Bay polar bear population. We used geographic positioning system and satellite collars deployed between 1991 and 2004 to quantify movement patterns of adult female polar bears on the sea ice of Hudson Bay in relation to reproductive class and temporal variations in sea ice patterns. We tested whether reproductive status and season affected movement and whether temporal changes in movement were correlated with temporal changes in sea ice patterns in Hudson Bay. Movement patterns were not dependent on reproductive status but did change significantly with season. Annual distances moved and areas covered by bears in Hudson Bay have decreased since 1991, which suggests that measured declines in bear condition and numbers are due to reduced prey intake as opposed to increased energy output. These declines in bear movement are correlated with progressively earlier ice break-up in western Hudson Bay.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".