Modelling the factors influencing ontogenetic dietary shifts in stream-dwelling brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Biotic and abiotic variables shape ontogenetic trajectories of animals. This study modelled (i) the body length related timing of the ontogenetic switch from aquatic to surface prey and (ii) the impacts of habitat characteristics, prey availability, and fish densities on the relative contribution of surface prey to the overall diet of native brown trout (Salmo trutta). We used individual-based models of dietary data for 170 fish (length range 48–343 mm). There was a high degree of individual variation in the use of surface prey, but logistic regression suggested that the shift from aquatic to surface prey was established at a body length of 81 mm (range 36–127 mm). Results of linear mixed-effects models highlighted the importance of fish length, benthic invertebrates, brown trout density, and water current velocity to the switch to surface prey by riverine brown trout, with fish length being the most influential variable. Our study provides evidence of the importance of ontogeny (intrinsic features of individuals linked to fish length) and individual differences in feeding behaviour to understand water-column use for feeding by stream-dwelling salmonids.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".