An Integrated Knowledge Translation Experience
Bibliographic record
Abstract
Pediatric audiologists lack evidence-based, age-appropriate outcome evaluation tools with well-developed normative data that could be used to evaluate the auditory development and performance of children aged birth to 6 years with permanent childhood hearing impairment. Bagatto and colleagues recommend a battery of outcome tools that may be used with this population. This article provides results of an evaluation of the individual components of the University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP) version 1.0 by the audiologists associated with the Network of Pediatric Audiologists of Canada. It also provides information regarding barriers and facilitators to implementing outcome measures in clinical practice. Results indicate that when compared to the Parents' Evaluation of Aural/Oral Performance of Children (PEACH) Diary, audiologists found the PEACH Rating Scale to be a more clinically feasible evaluation tool to implement in practice from a time, task, and consistency of use perspective. Results also indicate that the LittlEARS(®) Auditory Questionnaire could be used to evaluate the auditory development and performance of children aged birth to 6 years with permanent childhood hearing impairment (PCHI). The most cited barrier to implementation is time. The result of this social collaboration was the creation of a knowledge product, the UWO PedAMP v1.0, which has the potential to be useful to audiologists and the children and families they serve.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.055 | 0.014 |
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".