Predicting juvenile-to-adult survival in Chinook salmon using non-lethal scale-derived growth and regeneration indices
Bibliographic record
Abstract
Survival is often associated with body size, growth rate, and stress, but the latter two are more difficult to observe non-lethally. Non-lethal methods can be particularly important for endangered and culturally valuable species. With fish scales, growth and stress indices could be inferred without needing to sacrifice fish. We examined scales from ~350 wild Chinook salmon (Oncorhynchus tshawytscha) in Valley Creek and at Lower Granite Dam (Pacific Northwest, USA) in 2007–2019. From a von Bertalanffy model and scale circulus spacings, we estimated a brood-year-specific growth coefficient K (hereafter Kˆ). Using the scale-derived Kˆ and other biological and environmental covariates, we examined how these potential predictors associated with juvenile-to-adult survival of >136,000 passive-integrated-transponder-tagged Chinook salmon from the Snake River Basin (Pacific Northwest, USA). We found that the effects on survival from brood-year-specific Kˆ, fork length of the tagged individuals, and interaction between Kˆ and fork length were positive. We also determined that the proportion of fish samples with regenerated scales (an indicator of stress) had a negative effect on survival. For further refinement of non-lethal, scale-derived indices on survival, we encourage examination of indices across populations, juvenile habitats, and juvenile life stages, and not simply a regional, brood-year-specific growth index.
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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) | 0.000 | 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".