MétaCan
Menu
Back to cohort
Record W2343415715 · doi:10.1177/0194599816644407

Tablet Audiometry in Canada’s North

2016· article· en· W2343415715 on OpenAlexafffundabout
Ryan Rourke, David Chan Chun Kong, Matthew Bromwich

Bibliographic record

VenueOtolaryngology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern Ontario
FundersGrand Challenges Canada
KeywordsAudiometerAudiologyMedicineHearing lossAudiometryHearing testPopulationTest (biology)Environmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Access to hearing health care is limited in many parts of the world, creating a lack of prompt diagnosis, which further complicates treatment. The use of portable audiometry for hearing loss testing can improve access to diagnostics in marginalized populations. Our study objectives were twofold: (1) to determine the prevalence of hearing loss in children aged 4 to 11 years in Iqaluit, Nunavut, and (2) to test and demonstrate the use of our tablet audiometer as a portable hearing-testing device in a remote location. STUDY DESIGN: Prospective cross-sectional observational. SETTING: Remote elementary schools in 3 Canadian Northern communities. SUBJECTS AND METHODS: Tablet audiometers were used to test hearing in 218 children. Air conduction pure tones thresholds were obtained at 500, 1000, 2000, and 4000 Hz. Children with hearing loss ≥30 dB in either ear were referred for audiology services. RESULTS: Tablet audiometry screening testing revealed abnormal results in 14.8% of the study participants. No significant difference in the rate of hearing loss was seen by sex; however, the rate of hearing loss decreased significantly with increasing age. The median duration of the hearing test was 5 minutes 30 seconds. CONCLUSIONS: Of the study population, 14.8% tested positive for hearing loss based on our interactive tablet audiometer. In this setting, the tablet audiometer was both time efficient and largely language independent. This type of testing is valuable for providing much-needed hearing health care for high-risk populations in rural and remote areas where audiology services are often unavailable.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations54
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueOtolaryngologySame topicHearing Loss and RehabilitationFrench-language works237,207