Observable impairments predict mortality of captured and released sockeye salmon at various temperatures
Bibliographic record
Abstract
Migrating adult sockeye salmon frequently encounter commercial and recreational fishing gear, from which they may be landed, escape or be intentionally released. In this experiment, migratory adult sockeye salmon were exposed to simulated capture-release in fresh water, including 3 min of exhaustive exercise and 60 s of air exposure at three ecologically relevant water temperatures (13, 16 and 19°C) to understand how thermal and capture-release stressors may interact to increase mortality risk. Water temperature and sex were the factors that best predicted 24 and 48 h survival, with females in the warmest temperature group experiencing the greatest mortality. Capture-release treatment including air exposure was associated with equilibrium loss and depressed ventilation rates at release; the probability of fish surviving for 24 h after simulated capture-release was >50% if the duration of equilibrium loss was <2 min or ventilation frequency was >1 breath s(-1). Higher haematocrit and plasma lactate as well as lower mean cell haemoglobin concentration and plasma sodium and chloride 30 min after simulated capture-release were also significant predictors of 24 h survival. Together, the results demonstrate that simple observations that are consistent with physiological disturbance can be used as predictors for post-release short-term survival for sockeye salmon. The markedly higher post-stressor mortality observed in females demonstrates that managers should consider sex-specific variation in response to different fisheries interactions, particularly in the face of climate change.
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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) | 0.000 | 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".