Indicators of Energetic Status in Juvenile Coho Salmon and Chinook Salmon
Bibliographic record
Abstract
Abstract Bioenergetic models frequently rely on published values or models for estimating the energy density of fish, principally because of the cost and effort of obtaining direct measurements. In this study, we developed empirical models of energy density for free-ranging juvenile coho salmon Oncorhynchus kisutch and Chinook salmon O. tshawytscha sampled at sea from the west coast of Oregon to Kodiak Island, Alaska, and we evaluated the accuracy of published energy density models commonly used for these species. Our analyses showed that the energy density of juvenile coho and Chinook salmon was strongly correlated to percent dry weight and proximate constituents (especially lipid and, to a lesser extent, protein concentrations) but poorly correlated to body size and condition factor. Percent dry weight of whole fish was the single best predictor of energy density for both species, accounting for more than 90% of the variance in energy density. We also found that percent dry weight in the muscle tissue accounted for 65% of the variance in energy density. Changes in energy density mainly reflected changes in lipid composition. These results indicate that accurate estimates of energy density could be obtained at low effort and cost for juvenile coho and Chinook salmon simply by determining the water contents in whole-fish or muscle samples. Published models overestimate the energy density of juvenile coho and Chinook salmon collected from the Pacific Ocean. This may result from the extrapolation of the models to different size-classes, life stages, or habitats. More caution is needed when models are extrapolated to conditions beyond those that were used for their development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.000 | 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".