Deficits in the sensitivity to pitch sweeps by school-aged children wearing cochlear implants
Bibliographic record
Abstract
Sensitivity to static changes in pitch has been shown to be poorer in school-aged children wearing cochlear implants (CIs) than children with normal hearing (NH), but it is unclear whether this is also the case for dynamic changes. Yet, dynamically changing pitch has considerable ecological relevance in terms of natural speech, particularly aspects such as intonation, emotion, or lexical tone information. This study examined children and adults, with NH or wearing a CI using clinically assigned settings with envelope-based coding strategies. Percent correct was measured in one- or three-interval two-alternative forced choice tasks, for the direction or discrimination of harmonic complexes based on a linearly rising or falling fundamental frequency. Sweep rates were adjusted per subject, in a logarithmic scale, so as to cover the full extent of the psychometric function. Data for up- and down-sweeps were fitted separately, using a maximum-likelihood technique. Hits and false alarms were then converted into d’ and beta values, from which a threshold was extracted at a d’ of 0.77. Thresholds were very consistent between the two tasks and considerably higher (worse) for CI listeners than for their NH peers. Thresholds were also higher for children than adults. Factors such as age at implantation, age at profound hearing loss, and duration of CI experience did not play any major role in this sensitivity. Sweep direction thresholds held the most predictive power for performance in tasks related to speech prosody.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".