Comparison of Adult Steelhead Migrations in the Mid‐Columbia Hydrosystem and in Large Naturally Flowing British Columbia Rivers
Bibliographic record
Abstract
Abstract The migration of 1,263 adult radio‐tagged steelhead Oncorhynchus mykiss was assessed in the Nass, Skeena, Bella Coola, Fraser, and mid‐Columbia rivers from 1993 to 2001. Of the summer‐run steelhead tagged in the mid‐Columbia River, 80–87% eventually continued their upstream migration after being tagged, and 87–90% of those were detected in spawning areas. Similar results were seen for summer‐run steelhead tracked on the Nass and Skeena rivers. Mid‐Columbia summer‐run steelhead stocks that passed five dams en route to their spawning destinations (Methow and Okanogan rivers) traveled at a median rate of 20 km/d, which exceeded the median rates for summer‐run steelhead tracked on the Nass (3.8 km/d) and Skeena rivers (12–16 km/d). The upstream migration rates were best explained by river gradient and distance of the study area from the ocean. When the effects of river gradient and reach location were taken into account, impoundment was still a significant factor increasing the upstream migration speeds of summer‐run steelhead. Kelting speeds varied widely among rivers and did not appear to be a function of gradient.
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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 | 0.001 |
| 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".