Exposure to high temperature influences the behaviour, physiology, and survival of sockeye salmon during spawning migration
Bibliographic record
Abstract
Since 1996, some populations of Fraser River sockeye salmon ( Oncorhynchus nerka Walbaum in Artedi, 1792) have begun spawning migrations weeks earlier than normal, and most perish en route as a result. We suspect that a high midsummer river temperature is the principal cause of mortality. We intercepted 100 sockeye during normal migration near a spawning stream and measured somatic energy and aspects of plasma biochemistry. Fish were then held at either 10 or 18 °C for 24 days. Before release, fish were biopsied again and implanted with acoustic transmitters. A group of biopsied but untreated control salmon were released at the same time. Sixty-two percent (8 of 13) of control salmon and 68% (21 of 31) of 10 °C salmon reached spawning areas. The 18 °C-treated fish were half as successful (35%; 6 of 17). During the holding period, mortality was 2 times higher and levels of Parvicapsula minibicornis (Kent, Whitaker and Dawe, 1997) infection were higher in the 18 °C-treated group than in the 10 °C-treated group. The only physiological difference between treatments was a change in gill Na+,K+-ATPase activity. This drop correlated negatively with travel times for the 18 °C-treated males. Reproductive-hormone levels and stress measures did not differ between treatments but showed significant correlations with individual travel times.
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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".