Development and psychometric evaluation of the Persian version of the Phoneme Recognition Test: A central auditory processing measure.
Bibliographic record
Abstract
Objectives: The present study aimed to evaluate the psychometric properties of the Persian version of the Phoneme Recognition Test (P-PRT) in normal subjects and cochlear implant (CI) users. Material & Methods: This study includes developing the Persian phoneme recognition test (PRT), determining its validity and reliability, and comparing the results of a control group versus CI users. The test reliability was examined through a test-retest with an approximately five-week interval. In the present survey, 363 subjects were investigated in three stages. The face validity evaluation stage was conducted on 40 subjects. The psychometric properties of the P-PRT were evaluated in 323 individuals (225 normal subjects and 98 CI users). The test-retest reliability was examined in all the 225 subjects in the control group and 40 CI users. Results: The results confirmed the face validity of the P-PRT. No significant differences were observed between the two genders in terms of performance in the P-PRT. Significant differences were observed between the control and CI groups. Evaluating the test-retest reliability suggested perfect reliability (r>0.9) in both groups. Significant differences were observed in the P-PRT between the adults and the 7-year-old subjects compared to other age groups. Conclusion: The P-PRT can be used as a valid and reliable test for clinically evaluating phoneme recognition abilities and monitoring the rehabilitation progress.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".