Standard metabolic rate differs between rainbow trout (<i>Oncorhynchus mykiss</i>) growth forms
Bibliographic record
Abstract
In variable environments, repeatable phenotypic differences between individuals provide the variation required for natural selection. The pace-of-life syndrome (POLS) provides a conceptual framework linking individual physiology and life histories to behaviour, where rapidly growing individuals demonstrate higher rates of resting or “standard” metabolic rate (SMR). If differences in SMR are consistent between fast- and slow-growing individuals, these differences may be important to capture in bioenergetic relationships used to describe their growth, energy acquisition, and allocation. We compared growth rates and SMR between a domesticated and wild strain of rainbow trout ( Oncorhynchus mykiss (Walbaum, 1792)) using intermittent flow respirometry. Though mass-scaling exponents were similar between strains, mass-scaling coefficients of SMR for fast-growing rainbow trout were 1.25 times higher than those for slower growing fish. These observed differences in mass-scaling coefficients between fast- and slow-growing rainbow trout were consistent with data extracted from several other studies. Bioenergetic estimates of consumption for domestic strain fish increased as the difference in SMR and wild strain fish increased, and increased as activity level increased. Our results indicate patterns of SMR consistent with POLS, and suggest that strain-specific SMR equations may be important for applications to active populations (i.e., field observations).
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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".