Balance of peripheral input and integrity of the electrode-nerve interface in a large cohort of children with bilateral cochlear implants
Bibliographic record
Abstract
The study aim was to determine whether asymmetries in the electrode-nerve interface were present in children using bilateral cochlear implants (CIs). Bilateral CIs improve hearing over unilateral CIs in children with profound deafness in both ears but benefits decrease with increasing asymmetric activity and function between ears. Effects of asymmetry between bilateral CI arrays, CI stimulation parameters, impedance and transimpedance measurements, and electrophysiological thresholds could exacerbate asymmetries at the electrode-nerve interface but these factors have not been assessed in children using bilateral CIs. Clinically generated data from a large cohort of Canadian children (n = 669 children, n = 1332 devices) was gathered retrospectively for analyses. To account for repeated measures, a mixed effects modeling analysis was conducted. Despite CI electrical stimulation levels and electrophysiological thresholds being largely stable over time, asymmetries based on implantation sequence were observed. The observed bilateral differences suggest spread of current and sensitivity to electrical stimulation vary between devices in the same individual. These peripheral asymmetries may coincide with previously reported plasticity-induced cortical changes to increase asymmetries in auditory function between ears and restrict access to binaural hearing cues.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".