A simple method to assess the marine environment residence duration of juvenile sockeye salmon (<i>Oncorhynchus nerka</i>) using laser ablation
Bibliographic record
Abstract
Monitoring habitat utilization and early marine growth of sockeye salmon juveniles (Oncorhynchus nerka) in fjords of the Pacific Northwest is currently hampered by difficulties in estimating residence times, limiting scientific advances in certain aspects of this species’ fisheries management and conservation. Combining otolith microchemistry and conventional daily ring counts, we were able to obtain the date of first entry and the residence time of sockeye juveniles in Rivers Inlet, British Columbia. This operationally inexpensive method builds upon variable microelement concentrations in fresh- and saltwater environments: barium (Ba) and strontium (Sr) concentrations within the sockeye otoliths differed between the freshwater and seawater growth zones; Ba concentrations in the freshwater growth zone were significantly higher than those in the seawater growth zone, while Sr concentrations in the former were significantly lower than in the latter. The concentrations of these elements within otoliths were determined quantitatively at high spatial resolution using in situ laser ablation inductively coupled with a plasma mass spectrometer (ICPMS) providing a record of the ambient environmental conditions experienced by individual fish. Exploratory analysis of a 3-year data set showed that the mean residence time of sockeye juveniles in Rivers Inlet varied between 3 and 6 weeks between years.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".