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Record W4366990261 · doi:10.3389/fanim.2023.1180977

Investigating clove oil and its derivatives as anaesthetic agents for decapod crustaceans to improve welfare commercially and at slaughter

2023· article· en· W4366990261 on OpenAlexfundno aff
Felicity Spoors, Mark James, Tania Mendo, J. Chris McKnight, Eva‐Maria S. Bønnelycke, Nicola Khan

Bibliographic record

VenueFrontiers in Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersUniversity of St AndrewsTrent UniversityNottingham Trent University
KeywordsNephrops norvegicusShellfishCrustaceanFisheryAnimal welfareAmerican lobsterWelfareBiologyLawDecapodaEcologyHomarusFish <Actinopterygii>Political scienceAquatic animal

Abstract

fetched live from OpenAlex

Decapods have been recently classified as sentient beings in UK policy and therefore the establishment of humane methods for the live transportation and slaughter of commercially valuable shellfish as well as for decapods used in research is critical. Formerly overlooked, the use of anaesthetics provides a promising avenue for improving welfare standards for husbandry and slaughter for decapod crustaceans destined for human consumption or research. In particular, clove oil and its derivatives (eugenol and isoeugenol) have been trialled and recommended in literature as naturally-derived and effective, reversible anaesthetic compounds for a variety of decapods, including two commercially important British shellfish, brown crab (Cancer pagurus) and Norway lobster (Nephrops norvegicus). Further investigations should be undertaken to confirm the use of such anaesthetics is suitable for improving welfare standards in the British shellfish sector and in research to ensure that when the legislation changes, humane solutions are present.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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 designBench or experimental
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

Citations10
Published2023
Admission routes1
Has abstractyes

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