Acoustic measures of the cry characteristics of healthy newborns and newborns with pathologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Several hypotheses have been formulated as a result of observing spectrograms of the audio signals of the newborn infant cry in numerous studies. Our study is based on a few of these hypotheses. The purpose of this article is to differentiate pathological crying from healthy crying through acoustic cry analysis based on neurophysiological parameters of newborns. The automatic estimation of the characteristics of relevant cry signals, such as phonation, hyperphonation, and dysphonation, expressed as percentages, as well as unvoiced sound and mode change percentages, have enabled us to distinguish among the pathologies selected for this study. The results obtained have helped us to make quantitative associations between cry characteristics and pathological conditions affecting newborns.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it