MétaCan
Menu
Back to cohort
Record W29897128 · doi:10.1177/026119290403200507

Expanding the Three Rs to Meet New Challenges in Humane Animal Experimentation

2004· review· en· W29897128 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAlternatives to Laboratory Animals · 2004
Typereview
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversity of British Columbia
FundersUniversities Federation for Animal WelfareInternational Foundation for Ethical Research
KeywordsEngineering ethicsEnvironmental ethicsEngineeringPhilosophy

Abstract

fetched live from OpenAlex

The Three Rs are the main principles used by Animal Ethics Committees in the governance of animal experimentation, but they appear not to cover some ethical issues that arise today. These include: a) claims that certain species should be exempted on principle from harmful research; b) increased emphasis on enhancing quality of life of research animals; c) research involving genetically modified (GM) animals; and d) animals bred as models of disease. In some cases, the Three Rs can be extended to cover these developments. The burgeoning use of GM animals in science calls for new forms of reduction through improved genetic modification technology, plus continued attention to alternative approaches and cost-benefit analyses that include the large numbers of animals involved indirectly. The adoption of more expanded definitions of refinement that go beyond minimising distress will capture concerns for enhancing the quality of life of animals through improved husbandry and handling. Targeting refinement to the unpredictable effects of gene modification may be difficult; in these cases, careful attention to monitoring and endpoints are the obvious options. Refinement can also include sharing data about the welfare impacts of gene modifications, and modelling earlier stages of disease, in order to reduce the potential suffering caused to disease models. Other issues may require a move beyond the Three Rs. Certain levels of harm, or numbers and use of certain species, may be unacceptable, regardless of potential benefits. This can be addressed by supplementing the utilitarian basis of the Three Rs with principles based on deontological and relational ethics. The Three Rs remain very useful, but they require thoughtful interpretation and expansion in order for Animal Ethics Committees to address the full range of issues in animal-based research.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.419
GPT teacher head0.498
Teacher spread0.080 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it