An estimate of chinook salmon (<i>Oncorhynchus tshawytscha</i>) spawning habitat and redd capacity upstream of a migration barrier in the upper Columbia River
Bibliographic record
Abstract
Chief Joseph Dam on the Columbia River is the upstream terminus for anadromous fish because of its lack of fish passage facilities. Management agencies are currently evaluating the feasibility of reintroducing anadromous fish upriver of Chief Joseph Dam. We evaluated the physical characteristics of potential fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat in the upper section of Chief Joseph Reservoir. The objectives were to estimate the location and quantity of potential spawning habitat and to determine the redd capacity of the area based on spawning habitat characteristics. The suitability of the study area was estimated through the use of geomorphic analysis, empirical physical data, and modeled hydraulic data. We estimated that 5% (48.7 ha) of the study area contains potentially suitable fall chinook salmon spawning habitat. Potential spawning habitat is primarily limited by deep water and low water velocities, resulting in 20% (9.6 ha) of the potential spawning habitat being characterized as high quality. Estimates of redd capacity within potential spawning habitat range from 207 to 1599 redds. The results of our study provide fisheries managers with useful information for evaluating the complex issue of reintroducing anadromous fish to the Columbia River upstream of Chief Joseph Dam.
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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 | 0.000 | 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".