Tonic immobility as an anaesthetic for elasmobranchs during surgical implantation procedures
Bibliographic record
Abstract
Tonic immobility is a widely used technique for the surgical implantation of acoustic tags in elasmobranchs (sharks, skates, and rays), yet it is still not broadly recognised as an acceptable procedure by many regulatory bodies, animal care committees, and even journal ethics standards. To highlight its regular use and applicability as a field procedure, a literature search was conducted on the anaesthetic technique adopted for all existing elasmobranch-focused acoustic telemetry papers, up to 31 December 2013. A total of 57 studies were identified that contained relevant details on surgical methodological procedures. Of these, the majority of studies (43, or 75.4%) employed tonic immobility, while 10 (17.6%) used general chemical anaesthetic and 4 (7%) used local chemical anaesthetic. These studies identify that tonic immobility provides an effective anaesthetic for surgical implantation in elasmobranchs, as it offers several benefits over chemical anaesthetics, both from a practical and from an animal welfare perspective. Practically, rapid induction and recovery optimizes the surgical procedure, desirable under often complex field conditions, where general chemical anaesthetics prolong duration and administration is often unfeasible because of the size of study animals. Benefits over chemical anaesthetic for animal welfare include no risk of overdose, no uptake of chemicals to body tissues, minimal disruption to respiration, thereby reducing potential for negative sublethal impacts that influence postrelease behaviour, and immediate and full recovery. Given these benefits and its long-standing use in field studies, it is recommended that tonic immobility be recognised as an acceptable anaesthetic technique for surgical procedures on elasmobranchs.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".