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Record W4382502656 · doi:10.1080/14992027.2023.2227342

Derived-band auditory brainstem responses: cochlear contributions determined by narrowband maskers

2023· article· en· W4382502656 on OpenAlexafffund
David R. Stapells, Maxine R. Fok

Bibliographic record

VenueInternational Journal of Audiology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNarrowbandAudiologyBrainstemAuditory brainstem responseAuditory pathwaysCochleaAcousticsMedicineHearing lossPsychologyNeuroscienceComputer sciencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

OBJECTIVE: The present study sought to determine the cochlear frequency regions represented by Auditory Brainstem Responses (ABRs) obtained using the high-pass noise/derived response (HP/DR) technique. DESIGN: Broadband noise sufficient to mask the ABR to 50 dB nHL clicks was HP filtered (96 dB/oct) at 8000, 4000, 2000, 1000 and 500 Hz. Mixed with the clicks and HP noise masker was narrowband noise. Three derived response bands, denoted by the upper and lower high-pass noise frequencies, were obtained: DR4000-2000, DR2000-1000, and DR1000-500. STUDY SAMPLE: Ten adults with normal hearing, aged 19-27 years (mean age: 22.4 years), were recruited from the community. RESULTS: Frequencies contributing to each DR were determined from the wave V percent amplitude (or latency shift) vs narrowband masker frequency profiles (relative to a no-narrowband-noise condition). Overall, results indicate derived band centre frequencies were closer to the lower HP cut-off frequencies for DR4000-2000 and DR2000-1000, and approximately halfway between the lower HP cut-off and the geometric mean of the two HP frequencies for DR1000-500, with bandwidths of 0.5-1 octave in width. CONCLUSIONS: These results confirm the validity of the HP/DR technique for assessing narrow cochlear regions (≤1.0 octave wide), with centre frequencies within ½-octave of the lower HP frequency.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.328
Teacher spread0.307 · 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 designBench or experimental
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
Published2023
Admission routes2
Has abstractyes

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