Validation of an integrated pressure level measured earmold wideband real-ear-to-coupler difference measurement
Bibliographic record
Abstract
OBJECTIVE: To validate measurement of predicted earmold wideband real-ear-to-coupler difference (wRECD) using an integrated pressure level (IPL) calibrated transducer and the incorporation of an acoustically measured tubing length correction. DESIGN: Unilateral earmold SPL wRECD using varied hearing aid tubing length and the proposed predicted earmold IPL wRECD measurement procedure were completed on all participants and compared. STUDY SAMPLE: 22 normal hearing adults with normal middle ear status were recruited. RESULTS: There were no clinically significant differences between probe-microphone and predicted earmold IPL wRECD measurements between 500 and 2500 Hz. Above 5000 Hz, the predicted earmold IPL wRECD exceeded earmold SPL wRECDs due to lack of standing wave interference. Test-retest reliability of IPL wRECD measurement exceeded the reliability of earmold SPL wRECD measurement across all assessed frequencies, with the greatest improvements in the high frequencies. The acoustically measured tubing length correction largely accounted for acoustic effects of the participant's earmold. CONCLUSIONS: IPL-based measurements provide a promising alternative to probe-microphone earmold wRECD procedures. Predicted earmold IPL wRECD is measured without probe-microphone placement, agrees well with earmold SPL wRECDs and is expected to extend the valid bandwidth of wRECD measurement.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".