Effects of ontogeny, season, and temperature on the swimming performance of juvenile green sturgeon (<i>Acipenser medirostris</i>)
Bibliographic record
Abstract
Because some salmonids show decreased swimming performance (Ucrit) during their parr-smolt transformation, we tested the hypothesis that juvenile anadromous green sturgeon (Acipenser medirostris) decrease Ucritduring their analogous ontogenetic stage. Juvenile green sturgeon (mean age: 98 days) that had not reached seawater tolerance had a positive relationship of Ucrit(cm·s1) with total length (TL), whereas seawater-tolerant sturgeon (mean age: 150 days) had a negative relationship of Ucritwith TL. This Ucritdecrease was presumably seasonal because a similar-sized group of fish tested later (mean age: 288 days) showed a linear increase in Ucritwith TL. Smaller sturgeon displayed both morphological (larger relative pectoral fin surface areas) and behavioral (rostrum wedging and pectoral fin holding) attributes for station holding in a riverine environment. In a second experiment to test the effects of increased river temperature near the predicted time of downstream migration, Ucritand heat-shock protein concentrations increased at 24 °C compared with at 19 °C (mean age: 155 days). Thus, although there was evidence for cellular stress, the swimming ability of the fish was not compromised. Therefore, water velocity, temperature, and time of year should be considered in life-stage-specific efforts to manage or protect green sturgeon.
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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".