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Record W4402314999 · doi:10.1016/j.jecp.2024.106046

Social and communicative not a prerequisite: Preverbal infants learn an abstract rule only from congruent audiovisual dynamic pitch–height patterns

2024· article· en· W4402314999 on OpenAlexaff
Hiu Mei Chow, Yuen Ki, Chia‐huei Tseng

Bibliographic record

VenueJournal of Experimental Child Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsSt. Thomas University
FundersResearch Institute of Electrical Communication, Tohoku UniversityTohoku University
KeywordsPsychologyCognitive psychologyCommunicationDevelopmental psychology

Abstract

fetched live from OpenAlex

Learning in the everyday environment often requires the flexible integration of relevant multisensory information. Previous research has demonstrated preverbal infants' capacity to extract an abstract rule from audiovisual temporal sequences matched in temporal synchrony. Interestingly, this capacity was recently reported to be modulated by crossmodal correspondence beyond spatiotemporal matching (e.g., consistent facial emotional expressions or articulatory mouth movements matched with sound). To investigate whether such modulatory influence applies to non-social and non-communicative stimuli, we conducted a critical test using audiovisual stimuli free of social information: visually upward (and downward) moving objects paired with a congruent tone of ascending or incongruent (descending) pitch. East Asian infants (8-10 months old) from a metropolitan area in Asia demonstrated successful abstract rule learning in the congruent audiovisual condition and demonstrated weaker learning in the incongruent condition. This implies that preverbal infants use crossmodal dynamic pitch-height correspondence to integrate multisensory information before rule extraction. This result confirms that preverbal infants are ready to use non-social non-communicative information in serving cognitive functions such as rule extraction in a multisensory context.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score1.000

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)0.0100.000

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 head0.058
GPT teacher head0.449
Teacher spread0.390 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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