Preliminary assessment of the environmental and selective effects of a captive breeding and rearing programme for endangered Atlantic salmon, <i>Salmo salar</i>
Bibliographic record
Abstract
Abstract The selective and environmental effects of captivity on several fitness‐correlated traits were assessed in smolts of endangered Atlantic salmon, Salmo salar L., from the inner Bay of Fundy, produced via artificial spawning and released into the wild as juveniles. Smolts were sampled as they migrated downstream and identified through microsatellite‐based parentage analysis as offspring of either wild‐spawning adults or adults that were spawned in captivity. Overall, captive‐origin smolts exhibited a significantly later run timing and smaller body size than wild smolts. Significant differences in run timing and body size were also found between captive‐origin smolts that had experienced rearing environments that differed in duration of captivity and thermal regime. Significant differences in run timing, fork length and weight were found between first and second generation captive‐origin smolts, although the expression of these differences depended on the rearing environment experienced, suggesting a possible genotype by environment effect. The ratio of effective‐to‐census number of breeders that produced the captive‐origin smolts was higher than that of the wild‐origin smolts due to successful captive breeding management practices. These results have direct implications for captive breeding and rearing programmes for salmonids and wider implications for understanding the rates of evolutionary and environmentally induced change that can occur in captivity.
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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 | 0.001 | 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".