A simple and affordable calorespirometer for assessing metabolic rates of fishes
Bibliographic record
Abstract
Calorimetry is the measurement of the heat liberated during energy transformations in chemical reactions. When applied to living organisms, it measures the heat released due to the energy transformations associated with metabolism under both aerobic and anaerobic conditions. This is in contrast to the often-used respirometric techniques for assessing energy turnover, which can only be used under fully aerobic conditions. Accordingly, calorimetry is considered the 'gold standard' for quantifying metabolic rate, yet despite this, it remains a seldom-used technique among comparative physiologists. The reasons for this are related to the expense and perceived difficulty of the technique. We have designed and constructed an inexpensive flow-through calorespirometer capable of detecting rates of metabolic heat loss and oxygen consumption (O2) in fish under a variety of environmental conditions over long-term experiments. The metabolic heat of the fish is detected as a voltage by a collection of Peltier units wired in series, while oxygen optodes placed on the inflowing and outflowing water lines are used for the calculation of O2. The apparatus is constructed in a differential fashion to account for ambient temperature fluctuations. This paper describes the design and construction of the calorespirometer for ~$1300 CDN. Using the goldfish (Carassius auratus auratus), we show that the calorespirometer is sensitive to changes in metabolic rate brought about by pharmacological manipulation and severe hypoxia exposures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".