Heritability of fluctuating asymmetry for multiple traits in chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
The heritability of fluctuating asymmetry (FA) as an indicator of developmental instability is of interest to evolutionary and conservation biologists and is the subject of ongoing controversy. This study examined the inheritance of FA in two groups of fish: domestic chinook salmon (Oncorhynchus tshawytscha) mated in a full-sib design and domestic and wild chinook salmon mated in a half-sib design. Eight traits were measured on the right and left sides of each fish: eye diameter, head length, maxillary length, branchiostegal ray number, pectoral and pelvic fin ray number, and upper and lower gill raker number on the first gill arch. Narrow-sense heritabilities were calculated from parent-offspring regressions for the first group and using sib analysis for the second group. Our data represent the largest breeding program designed to detect heritability of FA in fish reported to date. We found no significant heritability of FA for any of the individual traits examined or for a composite FA index. Our results indicate that FA estimates in chinook salmon will not be confounded by appreciable additive genetic contributions and thus can be reliably used as an environmental and genetic stress indicator.
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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".