Comparison of Radiotelemetry and Microsatellites for Determining the Origin of Yukon River Chinook Salmon
Bibliographic record
Abstract
Abstract Chinook salmon Oncorhynchus tshawytscha support important subsistence and commercial fisheries throughout the Yukon River. Low returns and diverse user groups have made management of these fisheries contentious and have necessitated information on the origin of the spawning migration and harvest. Here we compare estimates of individual assignment and stock composition derived from genetic and radiotelemetry data collected from the same Chinook salmon. Radiotelemetry and genetic individual assignments were highly concordant. Agreement between methods for individual assignment was 79% to region and 93% to country when using the most probable genetic criterion, improving to 94% for region and 98% for country when using the ≥95% probability genetic criterion; however, under the more stringent criterion, fewer individuals could be assigned. Further analysis showed that estimates of stock composition based on radiotelemetry and genetic methods were within 6% of each other and were not significantly different. The concordance between estimates of individual assignment and stock composition from the radiotelemetry and genetic methods indicates that both methods are credible tools for fishery assessment of Yukon River Chinook salmon. Received October 14, 2011; accepted April 17, 2012
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".