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Record W4214609309 · doi:10.1017/9781009043359

Physiological Influences of Music in Perception and Action

2022· book· en· W4214609309 on OpenAlexaff
Shannon Wright, Valentin Bégel, Caroline Palmėr

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsPerceptionAction (physics)PsychologyActive listeningCognitive psychologyMusic perceptionMusic psychologyMusic and emotionCommunicationNeuroscienceMusicologyMusic educationMusic

Abstract

fetched live from OpenAlex

This Element reviews literature on the physiological influences of music during perception and action. It outlines how acoustic features of music influence physiological responses during passive listening, with an emphasis on comparisons of analytical approaches. It then considers specific behavioural contexts in which physiological responses to music impact perception and performance. First, it describes physiological responses to music that evoke an emotional reaction in listeners. Second, it delineates how music influences physiology during music performance and exercise. Finally, it discusses the role of music perception in pain, focusing on medical procedures and laboratory-induced pain with infants and adults.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.653
Threshold uncertainty score0.687

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 integrity0.0000.001
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 head0.090
GPT teacher head0.300
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations25
Published2022
Admission routes1
Has abstractyes

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