Genetic effects of ELISA-based segregation for control of bacterial kidney disease in Chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
We evaluated genetic variation in ability of Chinook salmon (Oncorhynchus tshawytscha) to resist two bacterial pathogens: Renibacterium salmoninarum, the agent of bacterial kidney disease (BKD), and Listonella anguillarum, an agent of vibriosis. After measuring R. salmoninarum antigen in 499 adults by enzyme-linked immunosorbent assay (ELISA), we mated each of 12 males with high or low antigen levels to two females with low to moderate levels and exposed subsets of their progeny to each pathogen separately. We found no correlation between R. salmoninarum antigen level in parents and survival of their progeny following pathogen exposure. We estimated high heritability for resistance to R. salmoninarum (survival h2 = 0.890 ± 0.256 (mean ± standard error)) independent of parental antigen level, but low heritability for resistance to L. anguillarum (h2 = 0.128 ± 0.078). The genetic correlation between these survivals (rA = –0.204 ± 0.309) was near zero. The genetic and phenotypic correlations between survival and antigen levels among surviving progeny exposed to R. salmoninarum were both negative (rA = –0.716 ± 0.140; rP = –0.378 ± 0.041), indicating that variation in antigen level is linked to survival. These results suggest that selective culling of female broodstock with high antigen titers, which is effective in controlling BKD in salmon hatcheries, will not affect resistance of their progeny.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".