Comparison of methods to quantify metabolic rate and its relationship with activity in larval lake sturgeon <i>Acipenser fulvescens</i>
Bibliographic record
Abstract
) during early life history stages, including fast-growing larval fish and even less focus on nonteleostean species. In the present study we evaluated measurement techniques for standard metabolic rate (SMR), maximum metabolic rate (MMR) and aerobic scope in an Acipenseriform, the lake sturgeon Acipenser fulvescens, throughout the first year of life. Standardized forced exercise protocols to assess MMR were conducted for 5 or 15 min before or after measurement of SMR. We used different levels of oxygen decline during the measurement period of MMR post forced exercise to understand the influence these may have on the calculation of MMR. Opercular rate and tail beat frequencies were recorded by video as measures of behaviours and compared to metabolic rate recorded over a 24 h period. Results indicate that calculated values for aerobic scope were lower in younger fish. Neither exercise sequence nor exercise duration influenced metabolic rate measurements in the younger fish, but exercise duration did affect measurement of MMR in older fish. Finally, there was no strong correlation between metabolic rate and the measured behaviours in the lake sturgeon at either age. Based on the results, we recommend that a minimum of 6 h of acclimation to the respirometry chamber should be given prior to measuring SMR, a chasing protocol to elicit MMR should ideally be performed at the end of experiment, a short chasing time should be avoided to minimize variation and assessment of MMR should balance measurement limitations of the probes along with when and for how long oxygen consumption is measured.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".