Short‐term Physiological Response Profiles of Tagged Migrating Adult Sockeye Salmon: A Comparison of Gastric Insertion and External Tagging Methods
Bibliographic record
Abstract
Abstract A variety of electronic tag types are routinely applied to fish to better understand migration biology. However, tagging procedures have the potential to affect the postrelease behaviour and survival of tagged individuals. In this study, wild adult Sockeye Salmon Oncorhynchus nerka from the Harrison River, British Columbia, were radio‐tagged by gastric insertion or external attachment techniques immediately after capture to understand the short‐term physiological response to these two tagging methods. Plasma cortisol, glucose, lactate, sodium, and potassium levels, as well as white muscle lactate and glycogen concentrations, were measured in samples obtained from fish upon capture (0 h) as well as 1 or 4 h after the tagging treatment. The effects of key biological variables, such as sex and proximity to spawn, on the physiological response to the tagging events were also evaluated. Tagging occurred during two distinct time periods representing fish of different maturation states and durations of freshwater residency. Overall, the physiological response to the tagging scenarios was characteristic of the disturbance associated with exhaustive exercise. There were no significant differences detected in the response profiles following gastric or external tagging procedures. This was despite procedural differences such as stomach perforations observed in 68% of the gastric insertions in the late sampling period, and external attachments taking three times longer (43 s) than gastric insertion (15 s). Moreover, the tagged fish showed similar response profiles to control fish that were handled but not tagged. These results suggest that the capture and handling associated with a tagging event induced physiological disturbance, and that the addition of a quick tagging procedure appeared to be nonadditive over the 4‐h assessment period. Sex and proximity to spawn had significant main and interaction effects on some of the physiological response variables, indicating that biological context is important for interpreting physiological assessments in experiments that manipulate exercise and stress responses in migrating adult Pacific salmon.
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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".