Mixed-Stock Analysis of Yukon River Chum Salmon: Application and Validation in a Complex Fishery
Bibliographic record
Abstract
Abstract Yukon River chum salmon Oncorhynchus keta are managed under the Pacific Salmon Treaty (PST), which requires conservation and equitable sharing of this fishery resource by the USA and Canada. Fall chum salmon are of special concern because they spawn in both the United States and Canada, and the focus of the PST is on Canadian-origin salmon. Yukon River chum salmon were assayed for genetic variation at 22 microsatellite loci to establish a baseline for mixed-stock analysis (MSA) applications to assist in addressing conservation and allocation issues. The baseline has been applied yearly to estimate the stock composition of Yukon River fall chum salmon from samples collected in the Pilot Station test fishery. Accuracies in MSA simulations for 12 of 14 management regions exceeded 90%, with a range of 80–98%, for the 12 most informative loci. Stock composition estimates were within 10% of the actual proportions in a known-origin mixture analysis. Stock-specific abundance estimates, which were derived from combining the estimates of genetic stock composition of Pilot Station test fishery harvests with sonar abundance estimates, were concordant with upriver escapement data. The combination of genetic MSA using the baseline developed in this study and sonar abundance provides a viable tool for assessing stock strength and assisting managers in regulating fisheries to maintain the productivity and evolutionary potential of Yukon River chum salmon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| 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".