Pediatric cochlear implantation: How much hearing is too much?
Bibliographic record
Abstract
Audiologic candidacy criteria for determining cochlear implantation candidacy in children are evolving. The objective of the study was to examine clinical practice related to the cochlear implantation of children who typically do not meet audiologic criteria for this technology. Practitioners' perspectives on the process and the factors influencing candidacy decisions were explored through focus group interviews with hospital and school-based practitioners. The interviews were analysed using qualitative techniques to identify key issues. The findings from the interviews informed a questionnaire which was sent to all cochlear implant centers in Canada to further examine clinician views and experiences with this special population. Responses were collected from 11 of the 12 centers and indicated that children with hearing outside typical criteria were receiving implants. The definition of 'borderline' varied across the programs from approximately 70 dB HL to less than 90 dB HL. All centers emphasized the importance of considering factors beyond the child's audiometric thresholds in candidacy decision-making.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".