To what extent do acute exposure and acclimation to cold temperatures \nimpact the cardiorespiratory capacity, stress response and swimming \nperformance of Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Limited research has been conducted on the physiology of Atlantic salmon (Salmo salar) \nat cold temperatures despite significant winter mortalities at sea-cage sites in Atlantic Canada. \nThus, I performed two experiments to investigate how acclimation to 8, 4 and 1°C, and acute \ncooling from 8-1°C, affected the Atlantic salmon’s cardiac function, metabolic capacity, stress \nphysiology and swimming performance. While this research shows that exposure to 1oC causes \nstress, and significantly reduces their metabolism and swimming performance, it also reveals that \nthere is significant flexibility/plasticity in how salmon modulate heart function when acutely vs. \nchronically exposed to cold temperatures. For example, the experiments were performed on \nsalmon from two different aquaculture companies, and changes in resting heart rate and size were \nonly seen in 1oC acclimated fish in Chapter 3. This data suggests that responses to cold \ntemperatures differ between cultured salmon populations. Further, how salmon meet the energetic \ndemands of exhaustive exercise depends on the duration of cold exposure [e.g., fish acutely cooled \nto 1℃ predominantly enhance tissue oxygen extraction, whereas those acclimated to this \ntemperature increase stroke volume]. These studies add greatly to our understanding of how \ntemperatures close to a salmon’s (fish’s) lower thermal limit impact its physiological capacity and \nthe mechanisms involved.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".