Variability of Lipids and Fatty Acids in Pacific Walrus Blubber
Bibliographic record
Abstract
The variability of lipid content and fatty acid (FA) composition across blubber depth and body sites are important considerations for condition and diet studies of marine mammals. We investigated lipid and FA variability among inner and outer blubber layers, three body sites, four study years, and lactation status of adult female Pacific walruses (Odobenus rosmarus divergens) using blubber samples collected from subsistence-harvested walruses in spring 2007–2010. Percent lipid content did not differ between the inner and outer blubber layers at the rump, flank, or sternum of walruses. Although FA composition differed between the inner and outer blubber layers, the difference was consistent across body sites, and differences between layers within individual FAs were small (<2%). Lipid content at the sternum of lactating females was 6% higher than non-lactating females, consistent with known variation in body condition among these reproductive classes. Across study years, lipid content varied 18% and individual FAs varied 6%, likely reflecting population-level interannual variability in energy budgets and small differences in diet among years. Consistency in blubber lipid content across blubber depth and body sites and detectable variation in blubber lipid content among reproductive classes and years suggests the potential for lipid content to be a useful indicator of walrus body condition. In addition to information on condition, FA composition of blubber samples could potentially provide insights into changes in walrus diet that may be expected to occur from changes in their access to prey resources resulting from continued sea ice loss.
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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 | 0.001 |
| 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".