Annual patterns of body, tissue, and organ mass variation in long-tailed ducks <i>Clangula hyemalis</i>
Bibliographic record
Abstract
Temporal variation in resource availability, physiological demands, and other factors are associated with many phenotypic changes in organisms. For example, there are often predictable stages of atrophy and hypertrophy in animals’ organs to accommodate changes in diet. Timing of stages may differ by sex given differences in life histories (e.g., egg-laying versus male–male competition). In this context, we quantified changes over the annual cycle in 153 long-tailed duck ( Clangula hyemalis) carcasses. We also tested whether timing of changes differed by sex. Total body mass was lowest in February and highest in November, whereas livers, spleens, kidneys, and salt glands were lightest in the middle of breeding seasons. Reductions in kidney and salt gland masses coincided with switches to using freshwater from marine habitats. Generally, timing in patterns of body mass change did not differ by sex. This was unexpected, and could arise from the compressed breeding season. We were also interested in evaluating whether changes in masses of tissues or organs were more dramatic for a species that breeds at such high latitudes than for species that breed at lower latitudes, but were unable to glean this information from the literature. We present coefficients of variation to facilitate future comparisons.
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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".