A Case Series Report: Prelingually Deaf Cochlear Implant Users and Factors Associated with Outcomes
Bibliographic record
Abstract
Approximately 219,000 people worldwide have received cochlear implants (CI) as of 2010. This retrospective study uniquely investigated three important components together including pre-lingual CI recipients (the most difficult-to-treat CI population), speech recognition before and after CI, and factors that may be associated with positive or negative speech recognition outcomes. Eight cases of pre-lingual CI users were selected, including four subjects with relatively better scores and four subjects with relatively poor scores. To compare these two groups, eight factors were investigated: gender; etiology; age of implantation; type of implant device; communication mode (oral, speech reading, or sign); patient compliance (attending scheduled clinic follow-up); family/environmental influence; and frequency using the CI device. Although the finding from this investigation is not statistically conclusive like other similar studies, it appears that some factors, such as patient compliance, oral communication, family environment, and/or the frequency using the CI device, may contribute to positive speech recognition outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".