Onset and maturation of fetal heart rate response to the mother’s voice over late gestation
Bibliographic record
Abstract
BACKGROUND: Term fetuses discriminate their mother’s voice from a female stranger’s, suggesting recognition/learning of some property of her voice. Identification of the onset and maturation of the response would increase our understanding of the influence of environmental sounds on the development of sensory abilities and identify the period when speech and language might influence auditory processing. AIM: To characterize the onset and maturation of fetal heart rate response to the mother’s voice. METHODS: 143 fetuses from 29 to 40 weeks gestational age (GA) received a standardized protocol: no-sound pre-voice baseline (2 min), audio recording of their mother reading a story (2 min), no-sound post-voice (2 min). The voice was delivered 10 cm above the maternal abdomen at an average of 95 dB A; heart rate was recorded continuously. RESULTS: For data analyses, fetuses were categorized into four age groups: 29–31, 32–34, 35–37, and > 37 weeks GA. Onset of response to the mother’s voice occurred at 32–34 weeks GA. From 32 to 37 weeks GA, there was an initial heart rate decrease followed by an increase. At term, there was a response shift to an initial heart rate increase. The percentage of fetuses responding increased over gestation from 46% at 32–34 weeks GA to 83% at term. CONCLUSION: A relatively long latency and sustained duration of the heart rate response suggest auditory processing, the formation of neural networks, above the level of the brainstem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".