Are Band Importance Functions Related to Conventional Speech Perception Outcomes in Adult Cochlear Implant Listeners?
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine if the pattern of an adult cochlear implant (CI) participant's band importance function (BIF) was associated with speech perception performance using standard assessments (i.e., consonant-nucleus-consonant [CNC] words, Arizona Biomedical [AzBio] sentences). DESIGN: A total of seven adults (nine ears) with CIs participated, along with nine adults with normal hearing (NH) as a control group. Each participant completed speech recognition measures (CNC word recognition and AzBio sentence recognition) in addition to BIF testing for six 1-octave-wide bands centered on frequencies between 256 and 8487 Hz using filtered monosyllabic words. RESULTS: The BIFs of NH and CI participants showed highest importance for mid-frequency bands. The BIFs for NH participants were uniform across participants with peak importance for the band with a center frequency around 2 kHz. BIFs for CI participants were variable, although, on average, they placed greater weight on the 2-kHz band. Additionally, the band with a center frequency of around 8 kHz carried the least importance for both groups. Higher speech perception outcomes were not obviously associated with a specific pattern of BIF among CI participants. CONCLUSION: Results of this study suggest that adults with CIs have more variable BIFs compared to adults with NH and that higher speech recognition outcomes are not associated with specific patterns of BIFs.
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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 | 0.003 |
| 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 | 0.000 |
| 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".