Landscape controls on boulder-rich, winter habitat availability and their effects on Atlantic salmon (<i>Salmo salar</i>) parr abundance in two fifth-order mountain streams
Bibliographic record
Abstract
We test the effect at river reach and segment scales of landscape controls on the distribution of Atlantic salmon (Salmo salar) parr densities, as well as associated variations in boulder (diameter ≥ 256 mm) abundance and potential overwintering habitat. This study encompasses data from 45 km of fifth-order mainstem channels along two neighbouring river catchments in the Gaspé region, Québec. At both scales, winter habitat availability was correlated with boulder availability. At the river segment scale (15 km), parr densities significantly correlated (P < 0.05) with boulder availability along the Bonaventure River, which presented significant intersegment variations in boulder abundances. In contrast, segment-scale boulder and parr abundances were uniformly low along the Petite Cascapédia River. At the reach scale (600 m), positive but less strongly significant boulder parr abundance correlations were observed in both the Bonaventure and Petite Cascapédia rivers. Spatial variations in boulder abundances in these systems reflected variations in the degree of channel to valley walls coupling and imposed channel formative shear stresses. In similarly boulder-poor segments with comparable fry abundances, parr abundances were significantly greater along the Bonaventure than the Petite Cascapédia River, possibly because of the presence in the former system of nearby boulder-rich refugia segments.
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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 | 0.000 | 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".