The role of a new contralateral routing of signal microphone in established unilateral cochlear implant recipients
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To investigate whether a contralateral routing of signal (CROS) microphone combined with a unilateral cochlear implant (CI) results in hearing improvement after a prolonged trial period. STUDY DESIGN: A prospective experimental trial was undertaken on a group of 10 postlingually deafened adults who are experienced CI users. METHODS: Participants completed audiometric testing and validated questionnaires with their unilateral CI alone, followed by addition of a CROS microphone (CI-CROS). This was worn daily for the 2-week trial, after which hearing performance was reevaluated using the same measures. Objective tests included AzBio sentences in quiet and noise and consonant-vowel nucleus-consonant (CNC) words. Subjective measures included the Abbreviated Profile of Hearing Aid Benefit (APHAB); Speech, Spatial, Qualities of Hearing Index (SSQ); Hearing Implant Sound Quality Index; an institutional questionnaire; and a daily log sheet. RESULTS: There is statistically significant enhanced speech discrimination with the CI-CROS when speech is presented on the CROS side. However, scores are markedly diminished when background noise is introduced, particularly to the CROS side. Subjective results indicate lower satisfaction scores for the global and ease of communication subdomains of the APHAB with the CI-CROS, but increased scores on the spatial hearing subdomain of the SSQ (P < 0.05). CONCLUSION: The CI-CROS provides significant benefit in certain situations, particularly speech recognition in quiet. CI-CROS performance with background noise is poor, leading to low satisfaction scores. Further refinement of the device may yield a useful tool for unilateral CI users in the future.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".