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Record W2075279414 · doi:10.1121/1.1861599

Sensory and nonsensory influences on children’s performance of dichotic pitch perception tasks

2005· article· en· W2075279414 on OpenAlexaff
Veronica Edwards, Deborah Giaschi, Pauline B. Low, Dorothy Edgell

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersMarch of Dimes Foundation
KeywordsDichotic listeningPerceptionSensory systemPitch perceptionAcousticsCognitive psychologyComputer sciencePsychologyAudiologyPhysicsNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Dichotic pitch perception reflects the auditory system's use of binaural cues to perceptually separate different sound sources and to determine the spatial location of sounds. Several studies were conducted to identify factors that influence children's dichotic pitch perception thresholds. An initial study of school children revealed an age-related improvement in thresholds for lateralizing dichotic pitch tones. In subsequent studies potential sensory and nonsensory limitations on young children's performance of dichotic pitch lateralization tasks were examined. A training study showed that with sufficient practice, young children lateralize dichotic pitch stimuli as well as adults, indicating an age difference in perceptual learning of the lateralization task. Changing the task requirements so that young children made a judgment about the pitch of dichotic pitch tones, rather than the spatial location of the tones, also resulted in significantly better thresholds. These findings indicate that nonsensory factors limit young children's performance of dichotic pitch tasks.

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)0.008
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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

Citations7
Published2005
Admission routes1
Has abstractyes

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Same venueThe Journal of the Acoustical Society of AmericaSame topicCognitive and developmental aspects of mathematical skillsFrench-language works237,207