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Record W2064790231 · doi:10.1037/0096-1523.34.3.693

Repetition priming in music.

2008· article· en· W2064790231 on OpenAlexafffund
Sean Hutchins, Caroline Palmėr

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMelodyRepetition (rhetorical device)Repetition primingTimbrePriming (agriculture)Tonic (physiology)Tone (literature)PsychologySpeech recognitionAudiologyCommunicationMathematicsComputer scienceLinguisticsNeuroscienceMusicalArtMedicineCognitionBiologyVisual arts

Abstract

fetched live from OpenAlex

The authors explore priming effects of pitch repetition in music in 3 experiments. Musically untrained participants heard a short melody and sang the last pitch of the melody as quickly as possible. Each experiment manipulated (a) whether or not the tone to be sung (target) was heard earlier in the melody (primed) and (b) the prime-target distance (measured in events). Experiment 1 used variable-length melodies, whereas Experiments 2 and 3 used fixed-length melodies. Experiment 3 changed the timbre of the target tone. In all experiments, fast-responding participants produced repeated tones faster than nonrepeated tones, and this repetition benefit decreased as prime-target distances increased. All participants produced expected tonic endings faster than less expected nontonic endings. Repetition and tonal priming effects are compared with harmonic priming effects in music and with repetition priming effects in language.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.127
GPT teacher head0.377
Teacher spread0.250 · 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 designObservational
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

Citations19
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Experimental Psychology Human Perception & PerformanceSame topicNeuroscience and Music PerceptionFrench-language works237,207