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Record W4397022542 · doi:10.3390/ani14101491

Music and Emotions in Non-Human Animals from Biological and Comparative Perspectives

2024· article· en· W4397022542 on OpenAlexaff
Juliana Zapata Cardona, Maria Camila Ceballos, Berardo de J Rodríguez

Bibliographic record

VenueAnimals · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Calgary
FundersInstituto Colombiano de Crédito Educativo y Estudios Técnicos en el ExteriorUniversidad de AntioquiaMinisterio de Ciencia, Tecnología e Innovación
KeywordsAnimal welfareNon-humanPerceptionWelfarePsychologyHuman animalHuman healthOrganismHuman welfareProductivityCognitive psychologyBiologyNeuroscienceMedicineEcologyLivestockPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The effects of sound stimulation as a sensorial environmental enrichment for captive animals have been studied. When appropriately implemented for farm animals, it can improve welfare, health, and productivity. Furthermore, there are indications that music can induce positive emotions in non-human animals, similar to humans. Emotion is a functional state of the organism involving both physiological processes, mediated by neuroendocrine regulation, and changes in behavior, affecting various aspects, including contextual perception and welfare. As there is very limited information on non-human animals, the objective of this review is to highlight what is known about these processes from human biological and comparative perspectives and stimulate future research on using music to improve animal welfare.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.098
GPT teacher head0.370
Teacher spread0.272 · 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 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

Citations9
Published2024
Admission routes1
Has abstractyes

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