Adult Sockeye Salmon Gastrically Tagged Near Spawning Grounds Exhibit Lower Survival Rates throughout the Spawning Period than Externally Tagged Conspecifics
Bibliographic record
Abstract
Abstract Telemetry is a common tool for studying the behavior and fate of migrating adult Pacific salmon Oncorhynchus spp., yet few field studies have compared behavior and fate associated with different tagging techniques. In this study, adult Harrison River (British Columbia) Sockeye Salmon O. nerka were captured in their natal river near spawning areas, radio-tagged by gastric insertion or external attachment in the dorsum, and released. Tagging occurred on 5 d spread over 3–8 weeks prior to spawning, thus encompassing fish in varying stages of maturity and freshwater residency. Tagged individuals were monitored over the spawning season by using fixed receiver stations and mobile tracking. The probability of fish moving upstream or downstream of the tagging site within 35 h of tagging was a function of tagging date but not tag type. Tag type significantly influenced fate, with almost twice as many externally tagged fish (41.6%; 42 of 101) surviving to reach spawning areas compared to gastrically tagged fish (22.4%; 21 of 94). The number of active externally tagged fish in the Harrison River system was consistently greater than the number of active gastrically tagged fish that received tags on the same date for four of the five tagging dates. External tag attachment may be a better approach than gastric insertion for studies that tag adult salmon near or on spawning areas.
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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) | 0.002 | 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".