Sea-to-sea survival of late-run adult steelhead (<i>Oncorhynchus mykiss</i>) from the Columbia and Snake rivers
Bibliographic record
Abstract
We used biotelemetry and genetic stock identification to assess sea-to-sea survival and run composition of 1212 late-migrating adult steelhead (anadromous Oncorhynchus mykiss) through the Columbia River and Snake River migratory corridors. The late run was predominated by steelhead from Idaho’s Clearwater and Salmon rivers that must pass eight large hydroelectric dams during both prespawn and postspawn migrations. In 2 years (2013 and 2014), prespawn survival to Snake River tributaries (>500 km) was 0.48–0.67 for the most abundant populations and was higher for females and 1-sea fish (i.e., fish that spend one winter at sea). Annual survival from Snake River tributary entry to postspawn kelt status was 0.14–0.17, with higher survival for females and those without hatchery fin clips. Kelt outmigration survival was 0.31–0.39 past four Snake River dams and 0.13–0.20 past all eight dams and was highest for smaller kelts. Full-cycle adult freshwater survival (sea-to-sea) including 16 dam passage events was 0.01–0.02. Younger steelhead and those without fin clips survived at the highest rates. This study uniquely partitioned mortality across prespawn, reproductive, and kelt life history stages and informs management strategies for this conservation-priority metapopulation.
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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) | 0.001 | 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".