Differential time budgets of two forms of juvenile brook charr in the open‐water zone
Bibliographic record
Abstract
No significant differences were found in the time budget (time spent in feeding, moving and stationary), attack rate (number of feeding bouts min−1), and microhabitat use of juvenile (1+ years) littoral and pelagic brook charr Salvelinus fontinalis at 2 and 4 m depth, when restricted to feeding in pelagic enclosures. In contrast, fish of the littoral form allocated significantly more time than pelagic ones to feeding, moving and in total activity at 3 m depth. No significant differences were found in attack rate between the two forms at any given depth. Based on the mean for the water column (all depths pooled), however, fish of the littoral form executed a significantly higher attack rate than fish of the pelagic one. In multiple regressions analyses, the best predictors of time allocated to feeding and attack rate were the dummy variable ‘form’ (littoral individuals spend significantly more time in feeding than pelagic ones), light intensity at the surface (negative) and water temperature (positive), and explained 48 and 55% of these variations, respectively. Time allocated to moving was only explained by water temperature (negative) and explained 43% of the variation. Time in a stationary position was best explained by water temperature (negative) and light intensity at the surface (positive), explaining 52% of the variation. The results of this study support the hypothesis that littoral brook charr spend more energy in foraging than pelagic ones when restricted to feeding in the pelagic habitat, and thus that trophic diversification is adaptive in this species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".