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Record W2140920944 · doi:10.4081/audiores.2013.e2

Are Open-Fit Hearing Aids A Possible Alternative to Bone-Anchored Hearing Devices in Patients with Mild to Severe Hearing Loss? A Preliminary Trial

2013· article· en· W2140920944 on OpenAlexaff
Amberley Ostevik, Rachel Caissie, Janine Verge, Mark Gulliver, William Hodgetts

Bibliographic record

VenueAudiology Research · 2013
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsCovenant Health
Fundersnot available
KeywordsAudiologyHearing lossHearing aidConductive hearing lossMedicineSpeech perceptionQUIETLoudnessHearing testPerceptionPsychology

Abstract

fetched live from OpenAlex

Open-fit hearing aids (OFHAs) may be of benefit for some individuals with chronic outer and middle ear conditions for which boneanchored hearing devices (BAHDs) are normally recommended. The purpose of this study was to compare performance between OFHAs and BAHDs. A Starkey Destiny 800 OFHA was fit on eight adult BAHD users and speech perception measures in quiet and in background noise were compared under two different test conditions: i) BAHD only and ii) OFHA only. Equivalent outcome measure performance between these two conditions suggests that the OFHA was able to provide sufficient amplification for mild to moderate degrees of hearing loss (pure-tone averages (PTAs) less than 47 dB HL). The improved speech perception performances and increased loudness ratings observed for several of the participants with moderately-severe to severe degrees of hearing loss (PTAs of 47 dB HL or greater) in the BAHD only condition suggest that the OFHA did not provide sufficient amplification for these individuals. Therefore, OFHAs may be a successful alternative to the BAHD for individuals with no more than a moderate conductive hearing loss who are unable or unwilling to undergo implant surgery or unable to wear conventional hearing aids due to allergies, irritation, or chronic infection associated with the ear being blocked with a shell or earmold.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.025
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.178
GPT teacher head0.411
Teacher spread0.233 · 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
Published2013
Admission routes1
Has abstractyes

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