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Spinal modulation of nociception by music

2012· article· en· W1519075020 on OpenAlexafffund
Mathieu Roy, Ariane Lebuis, Laurent Hugueville, Isabelle Peretz, Pierre Rainville

Bibliographic record

VenueEuropean Journal of Pain · 2012
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound ResearchInstitut Universitaire de Gériatrie de Montréal
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsNociceptionPsychologyArousalReflexActive listeningFibromyalgiaNeuroscienceAudiologyMedicineCommunication

Abstract

fetched live from OpenAlex

Numerous studies have demonstrated the capacity of music to modulate pain. However, the neurophysiological mechanisms responsible for this phenomenon remain unknown. In order to assess the involvement of descending modulatory mechanisms in the modulation of pain by music, we evaluated the effects of musical excerpts conveying different emotions (pleasant-stimulating, pleasant-relaxing, unpleasant-stimulating) on the spinally mediated nociceptive flexion reflex (or RIII), as well as on pain ratings and skin conductance responses. The RIII reflex and pain ratings were increased during the listening of unpleasant music compared with pleasant music, suggesting the involvement of descending pain-modulatory mechanisms in the effects of musical emotions on pain. There were no significant differences between the pleasant-stimulating and pleasant-relaxing musical condition, indicating that the arousal of music had little influence on pain processing.

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)0.001
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
Metaresearch0.0000.001
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)0.0020.000

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 head0.063
GPT teacher head0.334
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 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

Citations61
Published2012
Admission routes2
Has abstractyes

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