Effect of temperature and current manipulation on smolting in Chinook salmon (Oncorhynchus tshawytscha): the relationship between migratory behaviour and physiological development
Bibliographic record
Abstract
We investigated the role of temperature and current on migration pattern and physiological change in Chinook salmon ( Oncorhynchus tshawytscha ) smolts. Chinook parr were implanted with passive integrated transponder tags and placed in circular tanks with directional current. Paired antennas in each tank allowed for the monitoring of movements with or against the current. Two temperature regimes, naturally increasing (warm) and constant (cool), were combined with high current (>0.5 m·s–1) and low current (<0.1 m·s–1) to create four experimental treatments. At 2-week intervals, fish were sampled for gill Na+,K+-ATPase activity and plasma cortisol concentration. Increasing temperature resulted in an earlier peak in movement than colder groups and showed a distinct peak in gill Na+,K+-ATPase activity. Current did not influence physiological parameters associated with smolting and was not found to initiate movement; movement was related to accumulated thermal units (ATU). The presence of a strong, directional current, however, resulted in a period of more defined movement, suggesting a possible influence of current once migration is underway. A combination of either photoperiod or ATU with gill Na+,K+-ATPase was most strongly linked to movement. ATU was also found to be more strongly correlated with the smolting process than daily mean temperature.
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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".