Experimentally derived incorporation rates and diet-to-tissue discrimination values for carbon and nitrogen stable isotopes in gray wolves (<i>Canis lupus</i>) fed a marine diet
Bibliographic record
Abstract
Recent studies have noted the differential effects of marine versus terrestrial diets on the carbon and nitrogen stable isotope (13C and 15N, respectively) diet-to-tissue discrimination values and incorporation rates for omnivorous and carnivorous mammals. Inaccurate estimates of these parameters may result in misrepresentation of diet composition or in the timing of diet shifts. Here, we present the results of a diet-switch experiment designed to estimate diet-to-tissue discrimination values and incorporation rates for tissues of gray wolves (Canis lupus Linnaeus, 1758) fed a diet of Pacific salmon (genus Oncorhynchus Suckley, 1861). Our results demonstrate substantial differences in both parameters between wolves maintained on a marine (salmon) diet and wolves maintained on terrestrially sourced prey (beef, Bos taurus Linnaeus, 1758). Increased awareness of the significance of marine resources to omnivorous and carnivorous consumers, like wolves, highlights the importance of phenomenological and mechanistic understandings of the effects of fish and other marine prey on dietary investigations based on stable isotopes.
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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 | 0.001 |
| 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) | 0.000 | 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".