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Record W51554960

Can Uhear me now? Validation of an iPod-based hearing loss screening test.

2012· article· en· W51554960 on OpenAlexaff
Jacek Szudek, Amberley Ostevik, Peter T. Dziegielewski, Jason Robinson-Anagor, Nahla Gomaa, Allan Ho

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAudiogramAudiologyAudiologistHearing lossMedicineAudiometryNeurotologyOtologyTest (biology)OtorhinolaryngologySurgeryHead and neck surgery
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the uHear iPod-based application as a test for hearing loss. METHODS: We recruited 100 adult participants through a single otology practice. Patients with otorrhea and cognitive impairment were excluded. All patients completed the uHear test in the clinic and in the sound booth and underwent a standard audiogram by the same audiologist. We compared the results of the uHear test to the standard audiogram. RESULTS: The uHear was able to correctly diagnose the presence of hearing loss (pure-tone average [PTA] > 40 dB) with a sensitivity of 98% (95% CI = 89-100), a specificity of 82% (95% CI = 75-88), and a positive likelihood ratio of 9 (95% CI = 6.0-16). Compared to the audiogram, the uHear overestimated the PTA among all ears by 14 dB in the clinic and by 8 dB in the sound booth (p < .0001). Compared to the audiogram, the uHear overestimated the PTA among ears with hearing loss by 6 dB in the clinic and by 4 dB in the sound booth. CONCLUSIONS: The uHear application is a reasonable screening test to rule out moderate hearing loss (PTA > 40 dB) and and is valid at quantifying the degree of hearing loss in patients known to have abnormal hearing.

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)0.001
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 score0.182
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.069
GPT teacher head0.279
Teacher spread0.210 · 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

Citations99
Published2012
Admission routes1
Has abstractyes

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