Enhanced growth reduces precocial male maturation in Atlantic salmon
Bibliographic record
Abstract
Summary 1. Understanding the proximate and ultimate mechanisms shaping the expression of alternative reproductive phenotypes is a fundamental question in life‐history evolution. Precocial maturation in fishes, one such alternative phenotype, has been thought to reflect rapid growth and/or energy accumulation; however, mechanistically linking these specific traits to discrete life‐history patterns is complex and poorly understood. 2. Here, we use growth hormone (GH) transgenic Atlantic salmon to elucidate the effects of intrinsically fast growth on precocial male maturation as parr (freshwater life stage). Despite facilitating growth to sizes typical of mature wild‐type parr, transgenesis did not influence maturation in the first year of life. In the second year, the number of maturing transgenic parr was only half that of non‐transgenic individuals. 3. By manipulating intrinsic growth and controlling for both environment and genetic background, this study provides direct empirical evidence suggesting that the physiological mechanisms promoting growth do not play a causative role in precocial male maturation in fishes. 4. In addition, this study provides the first empirical data on the relative incidence of precocial male maturation in GH transgenic and non‐transgenic Atlantic salmon and, therefore, provides valuable information for the ecological risk assessment process.
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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".