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Record W7132921591

Recognition of popular songs by children and adolescents with cochlear implants

2004· dissertation· W7132921591 on OpenAlexfundno aff
Tara Vongpaisal

Bibliographic record

VenueTSpace · 2004
Typedissertation
Language
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsCochlear implantMelodyPianoPitch contourTheme (computing)Pitch (Music)Speech perceptionMusic perception
DOInot available

Abstract

fetched live from OpenAlex

Cochlear implants, which are optimized for speech perception, provide users with good temporal resolution but poor pitch resolution. In the present study, we examined the music processing abilities of child and adolescent implant users and comparison groups of normally hearing children and adults. Specifically, we tested their identification of original and altered renditions of familiar recordings of popular songs. Cochlear implant users performed somewhat more poorly than age-matched hearing listeners on instrumental and bass-and-drum renditions that preserved a number of acoustic features of the original recordings. Dramatic differences between these groups were evident on piano renditions that presented the main melodic theme in a novel timbre. Age and working memory were associated with implant users' performance on the challenging piano renditions. Despite their poor pitch resolution, which makes the most common pitch steps in music (1 and 2 semitones) inaccessible, cochlear implant users provided favorable appraisals of all renditions.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.294
Teacher spread0.280 · 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
Published2004
Admission routes1
Has abstractyes

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