Cochlear Delay and Medial Olivocochlear Functioning in Children with Suspected Auditory Processing Disorder
Bibliographic record
Abstract
Behavioral manifestations of processing deficits associated with auditory processing disorder (APD) have been well documented. However, little is known about their anatomical underpinnings, especially cochlear processing. Cochlear delays, a proxy for cochlear tuning, measured using stimulus frequency otoacoustic emission (SFOAE) group delay, and the influence of the medial olivocochlear (MOC) system activation at the auditory periphery was studied in 23 children suspected with APD (sAPD) and 22 typically developing (TD) children. Results suggest that children suspected with APD have longer SFOAE group delays (possibly due to sharper cochlear tuning) and reduced MOC function compared to TD children. Other differences between the groups include correlation between MOC function and SFOAE delay in quiet in the TD group, and lack thereof in the sAPD group. MOC-mediated changes in SFOAE delay were in opposite directions between groups: increase in delay in TD vs. reduction in delay in the sAPD group. Longer SFOAE group delays in the sAPD group may lead to longer cochlear filter ringing, and potential increase in forward masking. These results indicate differences in cochlear and MOC function between sAPD and TD groups. Further studies are warranted to explore the possibility of cochlea as a potential site for processing deficits in APD.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".