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Severity of hyperacusis predicts individual differences in speech perception in Williams Syndrome

2011· article· en· W2154073999 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.

Bibliographic record

VenueJournal of Intellectual Disability Research · 2011
Typearticle
Languageen
FieldNeuroscience
TopicWilliams Syndrome Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHyperacusisPsychologyAudiologyWilliams syndromeSpeech perceptionPerceptionConsonantDevelopmental psychologyHearing lossCognitionMedicineNeuroscienceSpeech recognition

Abstract

fetched live from OpenAlex

BACKGROUND: Williams Syndrome (WS) is a neurodevelopmental disorder of genetic origin, characterised by relative proficiency in language in the face of serious impairment in several other domains. Individuals with WS display an unusual sensitivity to noise, known as hyperacusis. METHODS: In this study, we examined the extent to which hyperacusis interferes with the perception of speech in children and adults with WS. Participants were required to discriminate words which differed in one consonant of a cluster when these contrasts were embedded in a background of noise. RESULTS: Although the introduction of noise interfered with performance on a consonant cluster discrimination task equally in the WS and control groups, the severity of hyperacusis significantly predicted individual variability in speech perception within the WS group. CONCLUSIONS: These results suggest that alterations in sensitivity to input mediate atypical pathways for language development in WS, where hyperacusis exerts an important influence together with other non-auditory factors.

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)0.009
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.283
GPT teacher head0.376
Teacher spread0.093 · 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