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Record W2136754809 · doi:10.1111/1467-9280.02435

Effects of Experience on Fetal Voice Recognition

2003· article· en· W2136754809 on OpenAlexaff
Barbara S. Kisilevsky, Sylvia M. J. Hains, Kang Lee, Xing Xie, Hefeng Huang, Hai Hui Ye, Ke Zhang, Zengping Wang

Bibliographic record

VenuePsychological Science · 2003
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyStimulus (psychology)PerceptionAudiologyFetusDevelopmental psychologySpeech perceptionCommunicationNeuroscienceCognitive psychologyPregnancyMedicine

Abstract

fetched live from OpenAlex

The ability of human fetuses to recognize their own mother's voice was examined. Sixty term fetuses were assigned to one of two conditions during which they were exposed to a tape recording of their mother or a female stranger reading a passage. Voice stimuli were delivered through a loudspeaker held approximately 10 cm above the maternal abdomen and played at an average of 95 dB SPL. Each condition consisted of three 2-min periods: no stimulus, voice (mother or stranger), and no stimulus. Fetal heart rate increased in response to the mother's voice and decreased in response to the stranger's; both responses were sustained for 4 min. The finding of differential behavior in response to a familiar versus a novel voice provides evidence that experience influences fetal voice processing. It supports an epigenetic model of speech perception, presuming an interaction between genetic expression of neural development and species-specific experience.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.366
Teacher spread0.331 · 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

Citations512
Published2003
Admission routes1
Has abstractyes

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