Estimation of occupancy, density, and abundance of larval lampreys in tributary river mouths upstream of dams on the Columbia River, Washington and Oregon
Bibliographic record
Abstract
We estimated occupancy, density, and abundance of larval Pacific lamprey (Entosphenus tridentatus) and Lampetra spp. in tributary river mouths to impounded portions of the Columbia River, Washington and Oregon, using count data from deepwater electrofishing. Count data were analyzed by Bayesian methods using zero-inflated N-mixture models modified to include our experimentally derived estimate of capture probability of 0.70 (95% CI: 0.63–0.77). Lampetra spp. were only collected in river mouths in Bonneville Reservoir, while Pacific lamprey were also captured from river mouths in The Dalles and John Day reservoirs. In occupied river mouths, mean densities were commonly 0.2–0.3·m−2, but ranged from 0.18 to 1.72·m−2 for Pacific lamprey and 0.24 to 1.72·m−2 for Lampetra spp. Although there was spatial overlap, estimated density peaked in the Klickitat River mouth (556 600 larvae) for Pacific lamprey and in the Wind River mouth (544 800 larvae) for Lampetra spp. Our study demonstrates considerable larval rearing in river mouths to impounded portions of the Columbia River; however, information on survival is needed to evaluate the contribution of this production to population growth and conservation.
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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".