Evaluation of a simple technique for recovering fish from capture stress: integrating physiology, biotelemetry, and social science to solve a conservation problem
Bibliographic record
Abstract
We evaluate the utility of an inexpensive, portable recovery bag designed to facilitate recovery of fish from capture stress by combining physiological assays, biotelemetry, and social science surveys. Adult migrating Pacific salmon (Oncorhynchus spp.) were used as a model, since some of their populations are threatened. While catch-and-release is common, there is a need to ensure that it is sustainable. A social science survey revealed that anglers generally have positive attitudes towards recovery bag use, particularly if research identifies that such techniques could be effective. Physiological assays on pink salmon (Oncorhynchus gorbuscha) revealed benefits of both high- and low-velocity recovery, but high velocity was most effective with reduced plasma cortisol concentrations and similar plasma sodium and chloride concentrations as those found in controls at all recovery durations. A biotelemetry study on sockeye salmon (Oncorhynchus nerka) captured by anglers and stressed by air exposure then placed in recovery bags had 20% higher, but not significantly different, survival than no-recovery salmon. The integration of natural science and social science provides an important step forward in developing methods for promoting recovery of fish from capture.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".