Effects of Telemetry Transmitter Placement on Egg Retention in Naturally Spawning, Captively Reared Steelhead
Bibliographic record
Abstract
Abstract Maturing female anadromous salmonids receiving intraperitoneally implanted telemetry transmitters (tags) may experience difficulty depositing eggs during natural spawning. We allocated maturing adult female steelhead Oncorhynchus mykiss to three treatment groups: (1) fish whose tags were surgically implanted in the body cavity (internal), (2) fish whose tags were implanted between the skin and muscle tissue (subdermal), and (3) nontagged fish. The steelhead were then allowed to spawn in an experimental channel. Internally tagged females retained significantly more eggs than did the subdermally tagged and nontagged control groups; subdermally tagged and nontagged control fish did not differ significantly. Females in the internally tagged, subdermally tagged, and nontagged groups retained an average of 49, 11, and 2% of their eggs, respectively. The onset of sexual activity did not differ significantly among treatments. Postspawning mortality was 70% for internally and subdermally tagged females and 0% for nontagged females. Each research or monitoring program should weigh the costs associated with transmitter use (where they are known) against the value of information obtained and should carefully evaluate assumptions about transmitter effects. For these reasons, the use of electromyogram electrodes and other telemetry transmitters for monitoring imperiled fish populations should be employed with caution. We suggest that subdermal implantation techniques be considered in future studies during the reproductive period to reduce egg retention caused by internally implanted transmitters.
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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".