Current Research with Cochlear Implants at Arizona State University
Bibliographic record
Abstract
In this article we review, and discuss the clinical implications of, five projects currently underway in the Cochlear Implant Laboratory at Arizona State University. The projects are (1) norming the AzBio sentence test, (2) comparing the performance of bilateral and bimodal cochlear implant (CI) patients in realistic listening environments, (3) accounting for the benefit provided to bimodal patients by low-frequency acoustic stimulation, (4) assessing localization by bilateral hearing aid patients and the implications of that work for hearing preservation patients, and (5) studying heart rate variability as a possible measure for quantifying the stress of listening via an implant. The long-term goals of the laboratory are to improve the performance of patients fit with cochlear implants and to understand the mechanisms, physiological or electronic, that underlie changes in performance. We began our work with cochlear implant patients in the mid-1980s and received our first grant from the National Institutes of Health (NIH) for work with implanted patients in 1989. Since that date our work with cochlear implant patients has been funded continuously by the NIH. In this report we describe some of the research currently being conducted in our laboratory.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".