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Record W2124312014 · doi:10.1080/14992020902971349

Evaluation of nonlinear frequency compression: Clinical outcomes

2009· article· en· W2124312014 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Audiology · 2009
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsAudiologyHearing lossSpeech recognitionConsonantPsychologyHearing aidPsychoacousticsSpeech processingSpeech perceptionVowelComputer scienceMedicinePerception

Abstract

fetched live from OpenAlex

This study evaluated prototype multichannel nonlinear frequency compression (NFC) signal processing on listeners with high-frequency hearing loss. This signal processor applies NFC above a cut-off frequency. The participants were hearing-impaired adults (13) and children (11) with sloping, high-frequency hearing loss. Multiple outcome measures were repeated using a modified withdrawal design. These included speech sound detection, speech recognition, and self-reported preference measures. Group level results provide evidence of significant improvement of consonant and plural recognition when NFC was enabled. Vowel recognition did not change significantly. Analysis of individual results allowed for exploration of individual factors contributing to benefit received from NFC processing. Findings suggest that NFC processing can improve high frequency speech detection and speech recognition ability for adult and child listeners. Variability in individual outcomes related to factors such as degree and configuration of hearing loss, age of participant, and type of outcome measure.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.142
GPT teacher head0.471
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it