Effects of domestication on growth physiology and endocrinology of Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Selection programs for fish frequently target growth rate as a breeding goal, yet surprisingly little is known about which mechanisms underlying the growth process are being targeted. The aim of this study was thus to examine whether the process of artificial selection of Atlantic salmon (Salmo salar) that has resulted in higher growth rate resulted in underlying changes in the growth hormone (GH) insulin-like growth factor I (IGF-I) axis of endocrine growth regulation. This was tested by comparing similarly reared seventh-generation farm salmon with wild salmon from the principal founder population of the farm strain at three life stages. Not unexpectedly, the domesticated fish outgrew their wild counterparts; this was most evident in salt water, where they averaged three times the weight by the end. Pituitary GH content was positively correlated with growth rate and correspondingly was significantly higher in the faster growing domesticated fish than in the wild fish. Plasma GH levels were also significantly higher in the domesticated fish, whereas IGF-I levels did not differ. These findings provide some of the first direct evidence indicating a link between domestication selection for growth and its endocrine regulation, whereby individuals with more active endocrine growth regulatory components are targeted.
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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 | 0.000 | 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".