Validation of the clinical assistant for research and learning (CARL) for pure-tone audiometric procedures
Bibliographic record
Abstract
OBJECTIVE: To evaluate the validity, clinical utility, barriers and facilitators of the manikin-based audiometric simulator, Clinical Assistant for Research and Learning. DESIGN: The validity, clinical utility, barriers, facilitators and simulation accuracy were evaluated via an online questionnaire and in-person pure-tone audiometric assessments. STUDY SAMPLE: A total of 38 participants (age range 21-63) completed the study. All participants had formal training in pure-tone audiometric assessments. Participants were audiology students, registered practicing audiologists, hearing instrument dispensers, and undergraduate students. RESULTS: The programmed and measured audiograms had an absolute agreement within 5 decibel hearing level. Ease of use, clarity of workflow, realism, and feasibility in clinical practice were the reported facilitators, whereas cost and availability of technical support were the identified barriers to implementation. CONCLUSIONS: The manikin-based simulator was shown to be an accurate and valid tool in practicing pure-tone audiometric procedures. Clinical applications and future directions were also discussed.
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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 | 0.029 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".