Effectiveness of an integrated hatchery program: can genetic-based performance differences between hatchery and wild Chinook salmon be avoided?
Bibliographic record
Abstract
Performance of wild (W) and hatchery (H) spring Chinook salmon (Oncorhynchus tshawytscha) was evaluated for a sixth generation hatchery program. Management techniques to minimize genetic divergence from the wild stock included regular use of wild broodstock and volitional releases of juveniles. Performance of HH, WW, and HW (hatchery female spawned with wild male) crosses was compared in hatchery and stream environments. The WW juveniles emigrated from the hatchery at two to three times the rate of HH fish in the fall (HW intermediate) and 35% more HH than WW adults returned (27% more HW than WW adults). Performance in the stream did not differ statistically between HH and WW fish, but outmigrants (38% WW, 30% HW, and 32% HH fish) during the first 39 days of the 16-month sampling period composed 74% of total outmigrants. Differences among hatchery-reared crosses were partially due to additive genetic effects, were consistent with domestication (increased fitness for the hatchery population in the hatchery program), and suggested that selection against fall emigration from the hatchery was a possible mechanism of domestication.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".