Using the Auditory Brainstem Response Elicited by Within-Channel Gaps to Measure Temporal Resolution
Bibliographic record
Abstract
The Auditory Brainstem Response (ABR) can be used to measure the early temporal activity of the auditory system. A gap-in-noise ABR has been developed to measure the electrophysiological response to auditory stimulation without attending to the task. In the present study, 15 young adults passively listened to stimuli of various gap widths in separate sequences. In a single sequence, two identical 15 ms filtered noise bursts, with a center frequency of either 750 or 3750 Hz, were presented separated by a gap (2, 5, 10, 20, 30, 40 or 50 ms in duration), with the second noise burst followed by an interstimulus interval of no less than 50 ms. An ABR was recorded at the onset of the first noise burst before the gap (pre-gap) and at onset of the second noise burst (i.e. at the offset of the gap, post-gap). The amplitude of wave V elicited after the gap increased as the gap duration grew larger, whereas the wave V before the gap, the control, remained relatively constant. A significant difference was found between the amplitude of wave V elicited before and after the gap for gap durations equal to and below 20 ms and 5 ms, for 750 and 3750 Hz, respectively. The gap-in-noise ABR can potentially provide frequency-specific information for the study of temporal resolution in populations with a variety of hearing disorders.
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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 | 0.001 |
| 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) | 0.001 | 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".