MétaCan
Menu
Back to cohort
Record W4392782497 · doi:10.1093/toxsci/kfae022

Exploring rabbit as a nonrodent species for general toxicology studies

2024· article· en· W4392782497 on OpenAlexaff
Katie Sokolowski, Patricia V. Turner, Elise Lewis, Ronald L. Wange, Marie Fortin

Bibliographic record

VenueToxicological Sciences · 2024
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPharmaceutical industryEconomic shortageVeterinary DrugsMedicinePharmacologyGovernment (linguistics)BusinessBiotechnologyToxicologyVeterinary medicineBiology

Abstract

fetched live from OpenAlex

To avoid adverse events in humans, toxicity studies in nonclinical species have been the foundation of safety evaluation in the pharmaceutical industry. However, it is recognized that working with animals in research is a privilege, and conscientious use should always respect the 3Rs: replacement, reduction, and refinement. In the wake of the shortages in routine nonrodent species and considering that nonanimal methods are not yet sufficiently mature, the value of the rabbit as a nonrodent species is worth exploring. Historically used in vaccine, cosmetic, and medical device testing, the rabbit is seldom used today as a second species in pharmaceutical development, except for embryo-fetal development studies, ophthalmic therapeutics, some medical devices and implants, and vaccines. Although several factors affect the decision of species selection, including pharmacological relevance, pharmacokinetics, and ADME considerations, there are no perfect animal models. In this forum article, we bring together experts from veterinary medicine, industry, contract research organizations, and government to explore the pros and cons, residual concerns, and data gaps regarding the use of the rabbit for general toxicity testing.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.833
GPT teacher head0.535
Teacher spread0.299 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueToxicological SciencesSame topicAnimal testing and alternativesFrench-language works237,207