Over-the-fence cochlear implantation: is it worthwhile?
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to estimate the upper limit of speech perception for cochlear implant candidates. DESIGN: A retrospective chart review of more than 700 cochlear implant users was conducted. SETTING: All patients received their implant through the Quebec Cochlear Implant Program, which is a hospital- and rehabilitation centre-based program. METHODS: Charts from patients with preimplantation sentence recognition performance exceeding 40% were selected. Postoperative performance was compared with preoperative results. MAIN OUTCOME MEASURES: Sentence and word recognition was assessed with a multimedia auditory test battery. RESULTS: Comparison of pre- and postimplantation sentence recognition in the best aided condition shows some theoretical gain up to a 80 to 85% score for in-quiet sentence recognition tests before the surgery. Comparison of preimplantation sentence recognition in the best aided condition and postimplantation word recognition with the implant alone shows some gain up to a 60% score for in-quiet sentence recognition tests before the surgery. CONCLUSIONS: The speech perception selection criteria can confidently be expanded to 60% from a conservative perspective and even up to the 80% range if the use of a contralateral hearing aid is highly expected.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".