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Record W2775649292 · doi:10.1080/14992027.2017.1410585

Maturation of bone-conduction transcranial and forehead attenuation using a measure of sound pressure in the ear canal

2017· article· en· W2775649292 on OpenAlexafffund
Allison R. Mackey, William Hodgetts, Susan A. Small

Bibliographic record

VenueInternational Journal of Audiology · 2017
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchHealth Canada
KeywordsForeheadAudiologyEar canalSkullBone conductionMedicineAttenuationTemporal boneAnatomyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Although it is understood that bone-conduction (BC) hearing is different between infants and adults, few studies have attempted to explain why these differences exist. The main objective in this study was to better understand how properties of the developing skull contribute to the maturation of BC sensitivity through an indirect measurement of BC attenuation across the skull. DESIGN: Estimation of transcranial and forehead attenuation of pure-tone BC stimuli was conducted using sound pressure in the ear canal for a transducer placed on the skull ipsi- and contralateral to the probe ear and at the forehead. STUDY SAMPLE: Seventy-six individuals participated in the study, including 59 infants and children (1 month-7 years) and 17 adults. RESULTS: BC attenuation was greatest for young infants, and decreased throughout maturation. Attenuation from the forehead to the ipsilateral temporal bone was also greater compared to the transcranial measures for infants and children older than 10 months. CONCLUSIONS: These results provide evidence that physical maturation of the skull contributes to infant-adult differences in BC attenuation. Clinicians may consider these results, in combination with previous studies using physiological measures, when fitting infants and young children with bone-anchored hearing systems.

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)0.000
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 score0.159
Threshold uncertainty score0.134

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.053
GPT teacher head0.340
Teacher spread0.288 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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