Questioning the Usefulness of Stimulation Rate Changes to Optimize Perception in Cochlear Implant Users
Bibliographic record
Abstract
Research exploring the impact of stimulation rate modifications on perception in cochlear implant users continues to expand. The existing body of research remains contradictory, making it difficult to establish a clear consensus that could inform clinical recommendations. In this context, this article aims to question the usefulness of such adjustments as a clinical intervention beyond the initial fitting, particularly for optimizing non-speech processing. To do so, we combined an overview of the existing literature on the effects of stimulation-rate changes on speech and non-speech processing with a discussion of observational data. The current evidence base is sparse, often contradictory, and affected by interoperability challenges that limit cross-study comparability. Consequently, it is not possible to formulate robust, evidence-based clinical recommendations at this time. Clinicians should be cautious about implementing stimulation-rate adjustments beyond the initial fitting and should wait for more robust evidence to emerge before considering such changes.
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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 | 0.023 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".