Relationships between habitat characteristics and breeding population densities in sockeye salmon (<i>Oncorhynchus nerka</i>)
Bibliographic record
Abstract
We examine the importance of stream habitat characteristics in governing variation in spawning densities of sockeye salmon ( Oncorhynchus nerka ) across 32 streams in the Fraser River Basin, British Columbia, Canada. We used mixed-effects models to examine four competing hypotheses for the influence of abiotic stream characteristics acting on either adult salmon or embryo mortality. All models that received support using Akaike’s information criterion included stream characteristics that are associated with cover. These included the percent area of pools, percentage of the banks that were undercut, and large woody debris (in that order). These results suggest the importance of stream characteristics, which reduce risk of predation on adults, in determining spawning sockeye salmon densities. Thus, identification of a small number of physical characteristics of streams provides insight into ecological processes that determine population densities. This information can be used to quantify habitat quality, which can guide habitat prioritization for 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".