Elemental signatures in otoliths of hatchery rainbow trout (Oncorhynchus mykiss): distinctiveness and utility for detecting origins and movement
Bibliographic record
Abstract
Otolith chemistry in freshwater has considerable potential to reveal patterns of origin and movement, which would benefit traditional fisheries management and provide a valuable tool to curb the spread of invasive and illicitly stocked species. We evaluated the relationship between otolith and water chemistry for five markers (Ba/Ca, Mn/Ca, Sr/Ca, Zn/Ca, and 87Sr/86Sr) in rainbow trout ( Oncorhynchus mykiss ) using the existing hatchery system in Colorado and Wyoming, USA, to provide controlled, seminatural conditions. Otolith Ba/Ca, Sr/Ca, and 87Sr/86Sr reflected ambient levels, whereas Mn/Ca and Zn/Ca did not. Using only the markers correlated with water chemistry, we classified fish to their hatchery of origin with up to 96% accuracy when element and isotope data were used together. Large changes in 87Sr/86Sr were evident in otolith transects, although subtler changes in Sr/Ca were also detectable. Our results suggest the relatively few otolith markers that reflect ambient chemistry can discriminate among locations and track movements well enough to provide valuable insight in a variety of applied contexts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".