Does Choosing the ???Worse??? Ear for Cochlear Implantation Affect Outcome?
Bibliographic record
Abstract
OBJECTIVE: To determine whether choosing the "better" ear or the "worse" ear for cochlear implantation impacts performance outcome. DESIGN: Retrospective cohort study. SETTING: University teaching hospital-cochlear implant program. METHODS: Two groups of cochlear implantees were selected and matched based on clinical parameters, including duration of deafness/age at implantation, implant types, and processing strategies. Nineteen patients received an implant in his or her "better" ear of the two that had been amplified. An equal number of patients received an implant in the "worse" ear--an ear that was not amplified or was chosen to avoid causing oscillopsia; or if the patient was not willing to relinquish his or her hearing aid in the "better" ear based on subjective or objective criteria. Standard speech perception testing was performed. RESULTS: The average open-set speech perception responses at 1 year after implantation were as follows: word recognition score 40.4% and sentence recognition score 81% in the aided subjects (better ears); word recognition score 41.5% and sentence recognition score 84.5% in the unaided group (worse ears). CONCLUSION: No differences were found between the two groups of implantees. Choosing the "worse" ear for implantation did not appear to have a negative impact on performance outcome in this match-paired study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".