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Record W4210458409 · doi:10.3390/ani12030365

Lessons and Recommendations from a Pentobarbital Shortage: US and Canada 2021

2022· article· en· W4210458409 on OpenAlexaboutno aff
Kathleen A. Cooney, Lianna Titcombe

Bibliographic record

VenueAnimals · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortagePentobarbitalAnimal welfareCompanion animalMedicineBusinessVeterinary medicinePharmacologyBiology

Abstract

fetched live from OpenAlex

In 2021, a shortage in the supply of the euthanasia drug pentobarbital sodium affected animal care professionals around the world, including in the United States and Canada. Pentobarbital sodium is the drug of choice for companion animal euthanasia in both countries. The decreased availability of pentobarbital sodium affected a number of animal care industries, forcing conservation of the drug and the use of alternative methods and other agents to facilitate humane death for all manner of animal species. Veterinary medical groups, laboratory research institutions, and the animal sheltering industry worked together to identify the best path forward to maintain routine euthanasia practices and to protect the welfare of animals. This article aims to explore the reasons behind the shortage and to highlight the necessary responses and adjustments made in order to continue providing euthanasia services in North America. Recommendations for handling future pentobarbital shortages are included.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0110.005
Scholarly communication0.0080.006
Open science0.0050.005
Research integrity0.0150.015
Insufficient payload (model declined to judge)0.0190.003

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 head0.116
GPT teacher head0.373
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations9
Published2022
Admission routes1
Has abstractyes

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