Comparison of the Behavioral Consequences and Recovery Patterns of Largemouth Bass Exposed to MS‐222 or Electrosedation
Bibliographic record
Abstract
Abstract Fish are commonly sedated to render them immobile and thus easier to handle for research, veterinary, and aquaculture practices. Since sedation itself imposes a significant challenge on the targeted fish, the selection of sedation methods that minimize physiological and behavioral disturbance and recovery time is essential. Two popular sedation methods include the chemical tricaine methanesulfonate (MS‐222) and electrosedation. Although many studies have already investigated the physiological consequences of these methods, there is limited research examining the latent behavioral effects on fish. Using Largemouth Bass Micropterus salmoides as a model species, we compared the postsedation behaviors of fish that were sedated with either MS‐222 or electrosedation to those of a control group exposed to the same handling protocol. Immediately after sedation, fish exposed to either treatment demonstrated lower reflex scores than the control group. Time to resume regular ventilation did not differ between chemically sedated and electrosedated fish; however, electrosedated fish regained equilibrium faster (mean ± SE = 154 ± 20 s) than fish that were exposed to MS‐222 (264 ± 30 s). Locomotor activity and swimming performance were assessed at 5‐, 30‐, or 60‐min intervals, beginning after individuals had recovered from sedation sufficiently to regain equilibrium. For all postsedation intervals, locomotor activity was two times greater in the electrosedated group than in the control and MS‐222 groups. Other behavioral measures (refuge emergence time, activity level, and flight initiation distance) and swimming performance did not differ at 5, 30, or 60 min postrecovery for any of the treatment groups. Our results indicate that while both chemical and electrical sedation methods result in impairment (i.e., sedation) immediately after treatment, these behavioral effects do not persist beyond 5 min postrecovery, and the two methods have similar impacts on Largemouth Bass. However, we caution that these results cannot be extrapolated to other fish species without further study. Received September 27, 2016; accepted January 17, 2017 Published online April 3, 2017
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".