The Effectiveness of Semi-Natural Rearing of Coho Salmon(Oncorhynchus kisutch) at the Nitinat River Hatchery, British Columbia
Bibliographic record
Abstract
We compared: 1) rearing mortality, 2) size at release (mean length), 3) jack, male and female sizes, and 4) jack, female, and adult returns of coho salmon (Oncorhynchus kisutch) from three consecutive brood years reared at the Nitinat River hatchery using a conventional or a semi-natural rearing method. The semi-natural method included feeding restrictions, shading of the rearing ponds, lower rearing temperature and rearing densities, exposure to a predator and a volitional release. We found no significant effects of brood year or rearing method on rearing mortality; it was significantly lower during the marking to release phase than during the other two phases (eyed-egg to ponding, ponding to marking). Conventionally reared smolts were significantly longer. Conventionally reared males were longer. As a proportion of number of smolts released, semi-natural rearing produced 86% fewer jacks, the same proportion of females and 15% more adults. Adult production trends, described as marine survival rate (returning adults • smolt-1) for Nitinat River Hatchery coho, and as ln recruits • female spawner-1 for a nearby wild coho population, were similar. Jacking rates were lower in Nitinat River hatchery coho than for the nearby wild coho population. We concluded that the semi-natural rearing methodology produces adult fish more efficiently than the conventional rearing method does, and at 73% of the cost.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".