PANEL 3: POLAR BEAR STUDIES Further Notes on Polar Bear Denning Habits
Bibliographic record
Abstract
Polar bears construct maternity dens in the snow throughout their range. The Owl River maternity denning a r e a on the Manitoba coast of Hudson Bay, Canada, had a measured productivity of 100-150 cubs in 1970 and 1971. Maternity denning is now confirmed for the Twin Islands in James Bay, but estimates of productivity for James Bay and the Ontario coast of Hudson Bay should still be made. Female polar bea rs build a variety of dens in the vicinity of their winter dens and along their route a s they move to the sea ice. This makes the censusing of maternity dens and estimating of productivity difficult. The winter dens in Hudson and James bays differ from high arc t ic dens in that earth chambers a r e used, with snow dens added a s winter progresses. Summer denning occurs along the Manitoba and Ontario coasts of Hudson Bay, and on the islands in James Bay. Surface pits, shallow dens and deep burrows a r e the three basic types of ear th dens built. All three types appear to be con-structed for temperature regulation by the bears, but each type is sometimes used la ter for shelter, protection from insects, protection from other bea rs or for winter dens. These behavioural adaptations appear significant in delineating a discrete polar bear population for James Bay and southern Hudson Bay.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.071 | 0.008 |
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".