Effects of stock, coded-wire tagging, and transplant on straying of pink salmon (<i>Oncorhynchus gorbuscha</i>) in southeastern Alaska
Bibliographic record
Abstract
Straying of pink salmon (Oncorhynchus gorbuscha) from two wild stocks (intertidal and upstream) in southeastern Alaska was estimated. Secondary factors (coded-wire tagging and transplanting of the intertidal stock) that may influence straying were also evaluated. In 1996, 321 494 fry were marked with either coded-wire tags or pelvic-fin clips. A total of 3828 marked adults were recovered in their natal streams and 79 strays were recovered in streams within 60 km of the release sites. The overall estimated straying rate was 5.1%. Estimated straying for the intertidal stock (9.2%) was higher than straying of the upstream stock (3.7%) but was not statistically different due to high variance of the estimates. The proportion of fish straying was significantly greater (P = 0.01) for coded-wire-tagged than for pelvic-fin-clipped fish for the upstream but not for the transplanted stock. Straying and distribution of the transplanted stock were more similar to those of the upstream stock, which was endemic to the natal watershed and release site of the transplant, than to those of the intertidal stock, which was the donor stock for the transplant. Although tagging may influence straying, incubation and initial estuarine environment appear to be major determinants of the natural straying of pink salmon in southeastern Alaska.
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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 | 0.002 |
| 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".