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Record W1559022555 · doi:10.1002/dev.21084

Fetuses respond to father's voice but prefer mother's voice after birth

2013· article· en· W1559022555 on OpenAlexaff
Grace Y. Lee, Barbara S. Kisilevsky

Bibliographic record

VenueDevelopmental Psychobiology · 2013
Typearticle
Languageen
FieldHealth Professions
TopicInfant Health and Development
Canadian institutionsKingston General HospitalQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsAudiologySound (geography)PsychologyFetal heart rateFetusDevelopmental psychologyHeart rateMedicineCommunicationPregnancyAcousticsInternal medicine

Abstract

fetched live from OpenAlex

Fetal and newborn responding to audio-recordings of their father's versus mother's reading a story were examined. At home, fathers read a different story to the fetus each day for 7 days. Subsequently, in the laboratory, continuous fetal heart rate was recorded during a 9 min protocol, including three, 3 min periods: baseline no-sound, voice (mother or father), postvoice no-sound. Following a 20 min delay, the opposite voice was delivered. Newborn head-turning was observed on 20 s trials: three no-sound, three voice (mother or father), three opposite voice, three no-sound trials with the same segment of each parent's recording. Fetuses showed a heart rate increase to both voices which was sustained over the voice period. Consistent with prior reports, newborns showed a preference for their mother's but not their father's voice. The characteristics of voice stimuli that capture fetal attention and elicit a response are yet to be identified.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.041
GPT teacher head0.375
Teacher spread0.334 · 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

Citations102
Published2013
Admission routes1
Has abstractyes

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