In vivo digestibility trials of a captive polar bear (Ursus maritimus) feeding on harp seal (Pagophilus groenlandicus) and Arctic charr (Salvelinus alpinus).
Bibliographic record
Abstract
Energetic requirements of free-ranging polar bears are still poorly understood due to the limited information available. The need for such data is emphasized through imminent climatic changes impacting wild populations, and the recent development of energy-based population forecast models that are data-limited. We therefore conducted four feeding trials with a captive polar bear to investigate how 2 novel untested diets such as Arctic charr (Salvelinus alpinus) and harp seal meat/fat (Pagophilus groenlandicus) are digested and energetically utilized. Energy content, proximate nutrient values, digestive efficiency, metabolizable energy (ME) requirements, and body mass change associated with these 2 diets were quantified. The seal meat/fat diet (1:1 ratio) had a 1.5 times greater digestible energy content (kg DM basis) than the charr diet. Digestibility coefficients for nutrients (organic matter, crude protein, fat) of both diets were high (> 0.960), which corresponds well with other carnivores, and other fatty polar bear diets. Body mass increased significantly over the course of the feeding trials, consuming an average of 403 and 1149 kJ/kg BM 0.75 of ME per day of charr and seal meat/fat, respectively. It was discovered that daily energy requirements of our adult, non-reproducing polar bear was lower than previously estimated (~ 1.4 instead of 2 times basic metabolic rate). Despite our limitations, we provide baseline data that should be evaluated during further feeding trials.
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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 | 0.000 |
| 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".