Coupling non‐invasive physiological assessments with telemetry to understand inter‐individual variation in behaviour and survivorship of sockeye salmon: development and validation of a technique
Bibliographic record
Abstract
Approximately 200 km from the mouth of the Fraser River, British Columbia, Canada, adult sockeye salmon Oncorhynchus nerka, were gastrically implanted with radio transmitters without anaesthetic. Subsets of the transmitter implanted fish were also biopsied which included drawing blood from the caudal peduncle (3 ml), removal of gill tissue (0·03 g) and quantification of energetic status using a microwave fat meter. Several experiments were used to test the hypothesis that the biopsy had a negligible effect on the subsequent survival and migratory behaviour of transmitter implanted fish. In the first experiment, no difference was found in the survival (both 100%) or tag retention (both 100%) between the two treatment groups (transmitter implanted with and without biopsy) when fish were held in pens for 24 h in the marine environment. Similarly, in other experiments where fish were released to the ocean to resume their migratory journey, no statistical differences were found in the travel times of fish in the two treatment groups, or in the proportion of fish that passed in‐river telemetry checkpoints. These results indicated that the handling and biopsy methods produced similar levels of mortality and tag retention as the telemetry treatment alone and that any changes in behaviour between the two treatment groups did not adversely affect migration time. Based upon the evidence provided from the biotelemetry of >300 adult sockeye salmon, it was felt that this general type of approach could be applicable to other fish species.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".