Foraging, growth, and loss rate of young-of-the-year Atlantic salmon (<i>Salmo salar</i>) in relation to habitat use in Catamaran Brook, New Brunswick
Bibliographic record
Abstract
The ideal despotic distribution predicts that individuals occupying preferred habitats will have higher fitness than those in less preferred habitats, whereas the ideal free distribution predicts that average fitness will be equal in all habitats. To test between these two alternatives, we studied habitat use in relation to foraging, growth, and loss rates of 216 individually tagged young-of-the-year Atlantic salmon (Salmo salar). Fish were observed by snorkelling between 2 July and 4 September 1999 in Catamaran Brook, New Brunswick. In a multiple logistic regression, the variables that best discriminated between the habitats used and not used by fish were mean flow velocity and water depth; the fish preferred habitats of intermediate flow velocity (648 cm·s1) and depth (2039 cm). Fish in preferred habitats experienced higher levels of food abundance and had higher foraging rates but did not differ in body size or growth rate compared with those in less preferred habitats, perhaps because of higher energetic costs. In addition, loss rate did not differ significantly between preferred and less preferred habitats. Our data suggest that salmonid populations at low density may be better described by an ideal free distribution rather than by an ideal despotic one.
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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 | 0.000 |
| 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".