Retention and Stress Effects of Visible Implant Tags When Marking Western Silvery Minnow and Its Application to Other Cyprinids (Family Cyprinidae)
Bibliographic record
Abstract
Abstract Visible implant tags are commonly used in fisheries research to mark individuals or batches of fish as part of movement and mark–recapture studies. To be effective, these tags generally need to have high retention rates and little impact on the behavior or physiology of the marked individuals. We tested the retention rates of both visible implant elastomer (VIE) and visible implant alphanumeric (VIA) tags in 80–139-mm Western Silvery Minnow Hybognathus argyritis over a 104-d period. We also measured plasma cortisol and lactate to determine the impact of tagging on stress levels. We found that VIE tags had 100% retention and did not cause a significant increase in plasma cortisol levels, though plasma lactate levels were elevated in VIE treatment groups. Overall, VIE tags were found to be suitable for marking Western Silvery Minnow and similar species. Visible implant alphanumeric tags had 36% retention over 104 d and did not cause significant increases in plasma cortisol, though plasma lactate was elevated in the treatment group with both VIE and VIA tags. Given the high retention rates and low stress effects, VIE tags appear to be more beneficial for use with Western Silvery Minnow and similar-sized cyprinids. Received April 16, 2015; accepted July 29, 2015
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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 | 0.001 | 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".