The influence of flume length and group size on swimming performance in shortnose sturgeon <i>Acipenser brevirostrum</i>
Bibliographic record
Abstract
The main objectives of this study were to determine optimal methodologies to assess the general swimming performance of juvenile shortnose sturgeon Acipenser brevirostrum. Swimming densities (group v. individual swimming) and flume length (2 v. 1 m) were altered to verify if any of those variables affected performance (i.e. time to fatigue) during critical swimming (U(crit)) and endurance tests. Results for both U(crit) and endurance swimming were not significantly different between fish swum in groups of five or fish swum individually. The U(crit) values, however, were c. 22% higher for fish swum in a longer flume. Although swimming fish in groups did not improve swimming performance, group swimming lowered the variance of the data. Results also reveal that juvenile A. brevirostrum may not possess an ability to swim at high speeds (i.e. burst phase) for long periods.
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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) | 0.000 | 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".