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Record W1993973577 · doi:10.1155/2012/802715

Multiple-ASSR Interactions in Adults with Sensorineural Hearing Loss

2012· article· en· W1993973577 on OpenAlexafffund
Ieda Maria Ishida, David R. Stapells

Bibliographic record

VenueInternational Journal of Otolaryngology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchWorkSafeBC
KeywordsAudiologyMedicineSensorineural hearing lossHearing loss

Abstract

fetched live from OpenAlex

The multiple auditory steady-state response (multiple-ASSR) technique, where thresholds for up to 8 frequencies (4 in each ear) are obtained simultaneously, is currently of great interest for audiometric assessment of infants. Although threshold estimates using the multiple-ASSR appear to be reasonably accurate, it is not currently known whether it is more efficient to use multiple stimuli or single stimuli when testing individuals with sensorineural hearing loss (SNHL). The current study investigated the effect of single versus multiple simultaneous stimuli on the 80- and 40-Hz ASSRs in adults with normal hearing or SNHL. Results showed significant interactions (i.e., decreased amplitudes) for both ASSRs going from single to multiple stimuli in one ear. Going from multiple one ear to multiple two ears did not further reduce the amplitude of the 80-Hz ASSR. At the 40-Hz rate, however, there was a further amplitude decrease going from one-ear multiple to two-ear multiple stimuli. Importantly, these interactions did not differ between the normal-hearing and SNHL groups. Although supportive of the multiple-ASSR technique, there are likely situations where it is more efficient to use single stimuli. Future studies are required to assess these interactions in infants with varying degrees and configurations of hearing loss.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.086
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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 teacher head, 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

Citations16
Published2012
Admission routes2
Has abstractyes

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