Consequences of catch-and-release angling on the physiological status, injury, and immediate mortality of great barracuda (Sphyraena barracuda) in The Bahamas
Bibliographic record
Abstract
Abstract O'Toole, A. C., Danylchuk, A. J., Suski, C. D., and Cooke, S. J. 2010. Consequences of catch-and-release angling on the physiological status, injury, and immediate mortality of great barracuda (Sphyraena barracuda) in The Bahamas. – ICES Journal of Marine Science, 67: 1667–1675. Great barracuda (Sphyraena barracuda) are a common marine predatory fish readily captured by anglers (frequently as incidental bycatch while pursuing other gamefish) and are consequently released at high rates. A study was conducted in coastal waters of The Bahamas to evaluate how common angling techniques influence their physiological status, hooking injury, and immediate mortality. Post-angling blood glucose and plasma sodium levels increased with fight-time duration, though lactate levels increased only with longer blood sampling times. Concentrations of plasma chloride and potassium were not influenced by angling duration. We did not observe any differences in injury, bleeding, hook removal, or hooking depth among three types of artificial lure tested. Most fish were hooked in non-critical areas and experienced minimal or no bleeding at the hook site, so immediate mortality upon landing was negligible. Although great barracuda appear to be fairly resilient to physiological stress and injury associated with catch-and-release angling and immediate mortality was insignificant, they typically reside in habitats where post-release predation is possible. As such, efforts should be made to promote careful handling to ensure high rates of survival.
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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".