Attitudes of laboratory animal professionals and researchers towards carbon dioxide euthanasia for rodents and perceived barriers to change
Bibliographic record
Abstract
Evidence indicates that carbon dioxide (CO 2 ) induces negative affective states (including anxiety, fear and distress) in laboratory rodents, but many countries still accept it for euthanasia. Alternative methods (e.g. inhalant anaesthetic) may represent a refinement over CO 2 but are not widely adopted. We conducted an online survey of Canadian and European laboratory animal professionals and researchers ( n = 592) to assess their attitudes towards the use of CO 2 and alternative methods for rodent euthanasia using quantitative 7-point scale (from 1 (= strongly oppose) to 7 (= strongly favour) and qualitative (open-ended text) responses. CO 2 was identified as the most common method used to kill rodents, and attitudes towards this method were variable and on average ambivalent (mean ± SD score on our 7-point scale was 4.4 ± 1.46). Qualitative analysis revealed four themes relating to participant attitude: (a) the animal’s experience during gas exposure; (b) practical considerations for humans; (c) compromise between the animal’s experience and practical considerations; and (d) technical description of the procedure or policies. Many participants (51%) felt that there were alternatives available that could be considered an improvement over CO 2 , but perceived barriers to implementing these refinements. Qualitative analysis of these responses revealed five themes: (a) financial constraints; (b) institutional culture; (c) regulatory constraints; (d) research constraints; and (e) safety concerns. In conclusion, concerns regarding the use of CO 2 often focused on the animal’s experience, but barriers to alternatives related to operational limitations. New research is now required on to how best to overcome these barriers.
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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 | 0.037 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".