Interacting effects of behavior and oceanography on growth in salmonids with examples for coho salmon (<i>Oncorhynchus kisutch</i>)
Bibliographic record
Abstract
Positive and negative relationships between pre- and post-smolt growth rates in salmonids have been observed, but the mechanisms underlying these relationships are not understood. We hypothesize that growth at sea is controlled by interactions between behavior and ocean conditions and that no one relationship is correct. We present a growth model with habitat-specific rates of anabolism that allow resource acquisition to vary in response to the behaviorenvironment interaction. Our model predicts positive relationships between pre- and post-smolt growth rates when ocean resources have clumped, defensible distributions under which conditions that aggressive behaviors facilitate increased access to those resources. Negative relationships are predicted when resources are dispersed and aggressive behaviors are ineffective. We present data relating pre- and post-smolt growth rates for more than 15 stocks of coho salmon (Oncorhynchus kisutch). These data indicate that shortly after out-migrating, aggressive behaviors are not effective for securing resources in the ocean (i.e., there are negative or no relationships between pre- and post-smolt growth rates). As coho spend more time at sea, however, variability in environmental conditions can elicit a variety of growth responses.
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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 | 0.001 |
| 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) | 0.001 | 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".