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Record W2005508590 · doi:10.1121/1.4787708

Pitch discrimination in children using cochlear implants

2006· article· en· W2005508590 on OpenAlexaff
Amy McKinnon, Michael Kiefte

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCochlear implantAudiologyPitch perceptionPsychologyPerceptionSpeech perceptionMedicine

Abstract

fetched live from OpenAlex

Research in pitch perception by cochlear implant users has focused primarily on postlingually deafened adults. Little is currently known regarding the pitch perception abilities of those who are implanted at a very early age, yet many children receive cochlear implants when they are less than 2 years old. Given the effects of brain plasticity, it is conceivable that pitch perception by early cochlear implant users may be much better than that of their older counterparts. This study examines pitch discrimination thresholds in young cochlear-implant users between the ages of 4 and 16. A computer game was developed to determine difference limens for fundamental frequency in vowellike stimuli at three referent frequencies: 100, 200, and 400 Hz. Two different tasks were employed: pitchdiscrimination, in which subjects were asked whether two stimuli are same or different, and pitch ranking, in which participants determine which of two stimuli is higher in pitch. Normal-hearing matches were tested to control for maturational effects, and adult cochlear implant users were also tested to compare findings with other studies. [Work supported by the Nova Scotia Health Research Foundation.]

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.019
GPT teacher head0.282
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of America→Same topicHearing Loss and Rehabilitation→French-language works237,207→