HYDROLOGIC CORRELATES OF BULL TROUT (<i>Salvelinus confluentus</i>) SWIMMING ACTIVITY IN A HYDROPEAKING RIVER
Bibliographic record
Abstract
There is a growing need to develop quantitative relationships between specific components of river flow and the behavioural responses of fishes. Given this, we tested for an effect of hydrologic parameters on axial swimming muscle electromyograms of bull trout (Salvelinus confluentus) in a large hydropeaking river (river discharge ranging from 0 to 1790 m3/s) while controlling for other exogenous factors such as temperature and light intensity. Hourly mean discharge had a significant positive effect (R2 = 0.13–0.31; depending on the distance from the dam) on swimming muscle activity. Within-hour changes in river flow from 0 to 1045 m3/s did not elicit a hyperactive response in bull trout. When a subset of electromyogram transmitters were calibrated to swimming speed, we found there were periods, across a range of river discharges, when bull trout were not actively beating their tails—a behaviour documented in some bottom-dwelling species associated with moving water. Not including these periods of rest, bull trout swam at median hourly speeds of 0.53 body lengths per second. Understanding fish behaviour in the context of their physical environment may help explain population-level responses to hydrologic change. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.000 | 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".