Tablet Audiometry in Canada’s North
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".