Postexercise Physiology and Repeat Performance Behaviour of Free‐Swimming Smallmouth Bass in an Experimental Raceway
Bibliographic record
Abstract
We studied postexercise physiology and behaviour of smallmouth bass (Micropterus dolomieu) that voluntarily ascended experimental raceways of varying length (20-50 m) against water velocities ranging from 8 to 120 cm/s. Our first objective was to link mean swimming speed to metabolism using patterns in postexercise muscle glycogen, muscle lactate, and plasma lactate. Our second objective was to examine several behavioural indices (attempt rate, success rate, and recovery time between an ascent and a subsequent attempt) and determine whether patterns in these data reflected those from the physiological measurements. Postexercise muscle glycogen and plasma lactate data suggest that smallmouth bass powered swimming speeds up to 70-80 cm/s using energy from aerobic processes. However, lactate did not begin to accumulate in the white muscle until speeds in excess of 120-130 cm/s were reached. The behavioural parameters measured did not indicate the presence of a physiological threshold at 70-80 cm/s; however, patterns in all factors changed appreciably when fish maintained speeds in excess of 120-130 cm/s. Therefore, it is clear that behaviour and physiology are tightly linked in this species and that maximum aerobic swimming capacity may not limit performance (or re-performance) during short-duration swims.
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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 | 0.001 |
| 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".