Dominance relationships and behavioural correlates of individual spawning success in farmed and wild male Atlantic salmon, <i>Salmo salar</i>
Bibliographic record
Abstract
1 Variance in competitive ability among males should lead to a corresponding skew in reproductive success. Atlantic salmon (Salmo salar) males form dominance hierarchies during spawning, such that the dominant individuals are predicted to realize the highest reproductive success. However, the degree to which this occurs depends on various genetic and environmental factors. 2 We investigated the influence of the aquaculture environment on male Atlantic salmon behaviour during spawning in three experiments involving groups of either purely farmed or wild males, or mixed groups composed of equal numbers of farmed and wild fish. The objective of this study was to compare and contrast the formation of dominance hierarchies and relationships between aggression, courtship and spawning success in farmed and wild males. 3 Although farmed males did not establish dominance hierarchies as effectively as wild males, they courted and spawned with females in larger numbers and they frequently failed to release sperm when females released eggs. 4 Dominance structures established by wild males led to reliable behavioural correlates of spawning success; this was not the case among farmed males. 5 From the risk-assessment perspective, farmed males can be expected to have reduced spawning success, although the degree of reproductive inferiority of farmed relative to wild males depends upon rearing environment and the populations under consideration.
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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".