Clinical Application of the Persian Version of Buffalo Model Questionnaire by examining Its correlation with the Buffalo Model Test Battery
Bibliographic record
Abstract
Background and Aim: The Buffalo Model Questionnaire (BMQ) has been proposed for the screening, helping to diagnose and also monitoring the effect of rehabilitation on the improvement of Central Auditory Processing Disorder ((C)APD). In this regard, the applicability and accuracy of Persian-BMQ (P-BMQ) are evaluated by examining the correlation between the results of this questionnaire and the Buffalo model test battery. Methods: Overall, 254 children, normal and with Specific Learning Disorder (SLD) aged between 7–12 years old participated in this cross-sectional study. The questionnaire was completed by the parents of children who were subjected to the Buffalo model test battery evaluations. Results: In the normal group, the highest correlation (0.648) was shown between the Decoding (D) component of the P-BMQ with the Row Staggered Spondaic Word (RSSW) variable. In the SLD group, the highest correlation (0.318) was shown between the Variance-tolerance fading memory (V) component of the P-BMQ and the qualitative Persian version of the Phonemic Sentence Test (P-PST) variable. The highest correlation was considered to be between the D component of the P-BMQ with the Right Competitive word, started in the Left ear (RC-LEF) variable in the SSW test (0.498), and qualitative P-PST variable (0.471); and 0.360 between the V component of the P-BMQ and Persian version of the Speech in Noise with S/N=4 in the Left ear (P-SIN4L) of variable in the P-SIN test. Conclusion: P-BMQ is a useful screening tool complementing the Persian Buffalo model test battery for evaluating auditory processing evaluation in children. Keywords: Central auditory processing disorder; specific learning disorder; Buffalo model questionnaire
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".