Simulation of temporal aspects of auditory aging
Bibliographic record
Abstract
A jittering technique to disrupt the periodicity of the signal was used to simulate the effect of the loss of temporal synchrony coding believed to characterize auditory aging. In one experiment jittering was used to distort the frequency components below 1.2 kHz and in a second experiment the components above 1.2 kHz were distorted. To control for spectral distortion introduced by jittering, comparison conditions were created using a smearing technique (Baer and Moore, 1993). In both experiments, 16 normal hearing young adult subjects were presented with SPIN sentences in three conditions (intact, jittered, and smeared) at 0 and 8 dB SNR. When the low frequencies were distorted, speech intelligibility in the jittered conditions was significantly worse than in the intact and smeared conditions, but the smeared and intact conditions were equivalent. When the high frequencies were distorted, speech intelligibility was reduced similarly by jittering and smearing. On low-context jittered sentences, results for young adults mimicked results found previously for older listeners with good audiograms (Pichora-Fuller et al., 1995). It is argued that the jittering technique could be used to simulate the loss of neural synchrony associated with age-related changes in temporal auditory processing.
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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 | 0.002 |
| 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".