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Record W1918672000 · doi:10.1177/10298649100140s206

In the beginning: A brief history of infant music perception

2010· article· en· W1918672000 on OpenAlexaff
Sandra E. Trehub

Bibliographic record

VenueMusicae Scientiae · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de MontréalUniversity of Toronto
Fundersnot available
KeywordsMelodySalience (neuroscience)PerceptionPsychologyRhythmMusicalRealmCognitive psychologyActive listeningInfant developmentAuditory perceptionMusic perceptionDevelopmental psychologyCommunicationHistoryVisual artsArtAestheticsNeuroscience

Abstract

fetched live from OpenAlex

The study of infant music perception began in the 1970s—a time when young infants were considered incapable of holistic processing of auditory sequences. These limitations were reconsidered with the demonstration of infants’ configural processing of pitch and timing patterns, which presaged the vibrant field of study that unfolded over subsequent decades. The 1980s revealed the salience of melodic contour for infants as well as adult-like processing of pitch and timing patterns. The 1990s shed new light on intervals and scales, uncovering situations in which infant listeners outperformed their adult counterparts. Scholars in the new millennium have documented a number of factors that influence rhythm perception in infancy, including incidental exposure to music and the experience of movement during music listening. In addition, brain-based measures are shedding light on the musical sensitivities of newborn infants. In sum, the conception of infants vis-à-vis music has changed substantially over the past four decades. Moreover, research in this realm is influencing ongoing debate about the nature and origins of music.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0020.005
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.004

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 head0.044
GPT teacher head0.269
Teacher spread0.225 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations26
Published2010
Admission routes1
Has abstractyes

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