Abnormal Voicing in Children Using Cochlear Implants
Bibliographic record
Abstract
OBJECTIVES: To measure acoustic voice outcomes in children with bilateral cochlear implants and to compare these with established norms, as well as to determine whether these acoustic measures were influenced by duration of cochlear implant use, age at implantation, and overall "time in sound." DESIGN: Cross-sectional study. SETTING: Pediatric tertiary care cochlear implant center. PATIENTS: All children using bilateral cochlear implants who were followed up during a 4-month period at our implant center were invited to participate. Twenty-seven children (17 males and 10 females) aged 3 to 15 years were enrolled. Causes of deafness included congenital (n = 8), genetic (n = 8), meningitis (n = 3), cytomegalovirus (n = 2), and unknown (n = 6). The interval between first and second implantations ranged from simultaneous to 7.8 years (mean, 4.2 years). MAIN OUTCOME MEASURES: Children completed acoustic voice testing using a Computerized Speech Lab and a Multi-Dimensional Voice Program. Acoustic results were compared with those of children receiving unilateral implants and with normative data. RESULTS: Compared with established pediatric normative data, children with bilateral implants demonstrated poor control of long-term frequency perturbation and long-term amplitude perturbation when vocalizing sustained phonations (P < .001 for both). This finding was consistent with data previously reported in children using unilateral cochlear implants. Long-term control of frequency perturbation improved as children used their bilateral cochlear implants over time and was significantly influenced by overall time in sound (P = .02). CONCLUSIONS: Similar to unilateral cochlear implant users, children using bilateral implants have difficulty controlling long-term frequency perturbation and long-term amplitude perturbation during sustained phonations. These measures improved as the duration of usable hearing increases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".