Comparing Immobilization, Recovery, and Stress Indicators Associated with Electric Fish Handling Gloves and a Portable Electrosedation System
Bibliographic record
Abstract
Abstract Fish sedation facilitates safer handling of fish during scientific research or fisheries assessment practices, thus limiting risk of injury to fish and reducing stress responses. In recent years, there has been growing interest in using electricity to sedate fish; two methods include (1) lower‐voltage, non‐pulsed‐DC fish handling gloves (FHGs) that tend to only sedate fish while the gloves are touching the animal; and (2) a comparatively high‐voltage, pulsed‐DC Portable Electrosedation System (PES) that leads to galvanonarcosis. This study compared the physiological consequences of exposure to FHGs and PES in teleost fish. Bluegills Lepomis macrochirus and Largemouth Bass Micropterus salmoides were exposed to FHGs, PES, or a handling control for a 3‐min simulated surgery. Blood was then sampled at 0.5 and 4.5 h postexposure and was analyzed for blood glucose, blood lactate, and plasma cortisol concentrations. Opercular rates were monitored during surgery, at 2 min postsurgery, and 0.5 h postsurgery. At 24 h postsurgery, time to exhaustion (via a standardized swimming chase protocol) was assessed. Fish exposed to FHGs tended to exhibit lower opercular rates than fish that were sedated with the PES during simulated surgery. Cortisol levels of Largemouth Bass treated with FHGs were higher than those of fish sedated with the PES. Glucose levels recorded for Bluegills at 4.5 h postsurgery were higher with FHGs than with the PES. In both species, lactate was lower for fish treated with FHGs than for those treated with the PES. At 24 h posttreatment, Bluegills sedated with FHGs exhibited a longer time to exhaustion than those subjected to the PES, whereas Largemouth Bass sedated with the PES exhibited a longer time to exhaustion than those sedated with FHGs. Physiological responses to treatments were inconsistent between species. Further investigation to determine the optimal electrosedation method is required.
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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) | 0.001 | 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".