Evaluation of a revised indication for determining adult cochlear implant candidacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the use of monosyllabic word recognition versus sentence recognition to determine candidacy and long-term benefit for cochlear implantation. STUDY DESIGN: Prospective multi-center single-subject design. METHODS: A total of 21 adults aged 18 years and older with bilateral moderate to profound sensorineural hearing loss and low monosyllabic word scores received unilateral cochlear implantation. The consonant-nucleus-consonant (CNC) word test was the central measure of pre- and postoperative performance. Additional speech understanding tests included the Hearing in Noise Test sentences in quiet and AzBio sentences in +5 dB signal-to-noise ratio (SNR). Quality of life (QoL) was measured using the Abbreviated Profile of Hearing Aid Benefit and Health Utilities Index. RESULTS: Performance on sentence recognition reached the ceiling of the test after only 3 months of implant use. In contrast, none of the participants in this study reached a score of 80% on CNC word recognition, even at the 12-month postoperative test interval. Measures of QoL related to hearing were also significantly improved following implantation. CONCLUSION: Results of this study demonstrate that monosyllabic words are appropriate for determining preoperative candidate and measuring long-term postoperative speech recognition performance. LEVEL OF EVIDENCE: 2c. Laryngoscope, 127:2368-2374, 2017.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it