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Record W2158744770 · doi:10.1002/icd.655

Exploring the relationship between fetal heart rate and cognition

2010· article· en· W2158744770 on OpenAlexaff
Barbara S. Kisilevsky, Sylvia M. J. Hains

Bibliographic record

VenueInfant and Child Development · 2010
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsHabituationPsychologyNoveltyCognitionStimulus (psychology)Developmental psychologyContext (archaeology)FetusOrienting responseAuditory stimuliAudiologyNeuroscienceCognitive psychologyPerceptionMedicineSocial psychologyPregnancy

Abstract

fetched live from OpenAlex

Abstract A relationship between fetal heart rate (HR) and cognition is explored within the context of infant, child and adult studies where the association is well established. Lack of direct access to the fetus and maturational changes limit research paradigms and response measures for fetal studies. Nevertheless, neural regulation of HR shows a number of parallels with adult regulation, albeit immature. Discrimination, habituation and learning of auditory stimuli provide evidence of a relationship between fetal HR and cognition. Fetuses discriminate speech sounds, demonstrating a HR decrease to a stimulus change, indicating attention/orienting. They show habituation, a novelty response and dishabituation of a HR response to complex sounds and faster habituation over intervals of 10 min and 24 h, indicating memory. Differential HR response to the familiar mother's versus a novel stranger's voice and to a familiar versus novel passage demonstrate learning, suggesting that neural networks sensitive to the properties of ubiquitous environmental sounds are being formed before birth. Copyright © 2010 John Wiley & Sons, Ltd.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0010.000
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 head0.060
GPT teacher head0.265
Teacher spread0.205 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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