Directionality in BiCROS hearing aids: an investigation of objective and subjective outcomes
Bibliographic record
Abstract
OBJECTIVES: To assess the effect of forward and omnidirectional microphone configurations in BiCROS versus monaural hearing aids on objective and subjective outcomes in different noise conditions. DESIGN: After fitting and a 4-week acclimatisation period, speech recognition and sound quality were measured using forward directional, omnidirectional, and unaided settings. Two noise configurations were used, surrounding noise and noise presented from the aided (better) ear. Subjective outcomes were assessed using the SSQ-b and BBSS questionnaires and participant interviews. STUDY SAMPLE: Eighteen adult participants (mean: 74.6 y; range: 61-94 y; ten males, eight females) with mild to moderately severe SNHL in their better ear (PTA0.5-4khz > 20 dB HL) and limited usable hearing in their poorer ear (average PTA0.5-4khz > 100 dB HL). RESULTS: Significant improvement in speech recognition and sound quality for BiCROS and monaural directional settings over omnidirectional and unaided, in both noise configurations. There were no significant differences observed between monoaural and BiCROS directional settings. CONCLUSION: Speech in noise recognition and sound quality scores demonstrated a significant directional benefit for both BiCROS and monaural directional fitting settings over omnidirectional and unaided conditions. Unique BiCROS-specific experiences were identified in a patient-oriented approach. These can inform the development of BiCROS-tailored tools.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".