Complex relationships among rearing temperature, growth, and sprint speed in clonal lines of rainbow trout
Bibliographic record
Abstract
Cold-water dependent rainbow trout (Oncorhynchus mykiss) inhabit a considerably diverse geographic range extending from Alaska to southern California, where adjustments in growth and swim performance in response to temperature may be present. Here we measured four clonal lines of rainbow trout for growth and sprint speed, at two different constant temperatures (10 or 18 °C), across 12 weeks. The objective was to characterize temperature responses among different genotypes originating from Alaska, Oregon, and two hatchery populations; we expected that the lines would respond in a way that implicated their diversity in geographic origin and domestication history. We observed all fish achieve the greatest growth and body size and fastest sprint speed at 18 °C, regardless of origin; substantial variation in growth and swim performance among and within line and temperature was also observed. Surprisingly, the Swanson line from Alaska exhibited very rapid growth at the warmer temperature, which may support the countergradient variation in growth hypothesis. The diversity of responses reported here illustrates the complex nature of the relationship among temperature, growth, and performance and provide groundwork for future genetic analyses utilizing clonal lines of rainbow trout.
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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) | 0.000 | 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".