Effect of masker harmonicity on threshold: Auditory filter envelope-modulation rate variability versus equidistant spacing of partial frequencies
Bibliographic record
Abstract
In a previous paper [W. C. Treurniet and D. R. Boucher, J. Acoust. Soc. Am. 109, 306–320 (2001)], a model was presented which successfully accounted for the lower threshold obtained using a harmonic masker instead of a similar inharmonic masker. For the harmonic masker, the frequencies of partials were separated by a fixed amount, so the envelope modulation-rates of auditory filter outputs remained the same across filters. However, for the inharmonic masker, the interval between adjacent partials was not fixed and this resulted in a decreased uniformity of modulation-rates across filters. The model proposed that the lower uniformity impedes detection of a probe-induced change in the modulation rates, thus accounting for the masked threshold difference. This paper shows that an inharmonic masker yields results similar to a harmonic masker provided that the modulation rates are uniform across affected auditory filters. Thus, the lowered threshold associated with a harmonic masker appears to arise from invariant modulation-rates across auditory filters, and does not require that all partial-frequencies be integer multiples of a fundamental.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".