DERIVED-BAND AUDITORY BRAINSTEM RESPONSES: COCHLEAR CONTRIBUTIONS DETERMINED BY NARROWBAND MASKERS
Bibliographic record
Abstract
Abstract Objective The present study sought to determine the cochlear frequency regions represented by Audtory Brainstem Responses (ABRs) obtained using the high-pass noise/derived response (HP/DR) technique. Design Broadband noise sufficient to mask the ABR to 50 dB nHL clicks was HP filtered (96 dB/oct) at 8000, 4000, 2000, 1000 and 500 Hz. Mixed with the clicks and high-pass noise masker was narrowband noise. Three DR bands, denoted by the upper and lower high-pass noise frequencies, were obtained: DR4000-2000, DR2000-1000, and DR1000-500. Study sample Ten adults with normal hearing, aged 19-27 years (mean age: 22.4 years), were recruited from the community. Results Frequencies contributing to each DR were determined from the wave V percent amplitude (or latency shift) vs narrowband masker frequency profiles (relative to a no-narrowband-noise condition). Overall, results indicate derived band center frequencies were closer to the lower HP cutoff frequencies for DR4000-2000 and DR2000-1000, and approximately halfway between the lower HP cutoff and the geometric mean of the two HP frequencies for DR1000-500, with bandwidths of 0.5-1 octave in width. Conclusions These results confirm the validity of the HP/DR technique for assessing narrow cochlear regions (≤1.0 octave wide), with center frequencies within ½-octave of the lower HP cutoff frequency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".