Infants’ overlapping vocalizations during maternal humming: Contributions to the synchronization of preterm dyads
Bibliographic record
Abstract
Despite the neurological vulnerability of premature newborns, there is evidence that they are able to process temporal aspects of the maternal voice, as a previous study observed more overlapping vocalizations during maternal humming versus speech. However, there is a lack of knowledge about the markers of the infants’ overlapping vocalizations. Our aim was to identify the location of overlapping vocalizations during the humming and the impacts of maternal antenatal and postnatal engagement of infant-directed singing on: (1) the features of humming and (2) the infants’ overlapping vocalizations during humming. Preterm dyads ( N = 36) were observed in silent, speech, and humming conditions. Microanalysis was performed using the Elan Program to identify the location of the overlapping vocalizations during the humming phrase. Infants’ overlapping vocalizations were found predominantly at the ends of each humming phrase; almost half of the overlaps occurred on the final note. More overlapping vocalizations in the final notes were observed in female infants. Antenatal and postnatal experiences of ID singing are influenced by the mothers’ nationality and contribute to maternal humming style. Preterm newborns synchronize with maternal humming, anticipating the end of musical phrases. The ability to synchronize seems to be phylogenetically associated with gender differences.
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 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 | 0.003 |
| 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 | 0.001 |
| 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".