Masked threshold difference due to masker harmonicity: Uniform modulation rates of auditory filter outputs versus periodicity in waveform fine structure
Bibliographic record
Abstract
In a previous paper [Treurniet and 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 equally spaced, so the envelope modulation rates of auditory filter outputs were invariant across filters. However, for the inharmonic masker, the intervals between adjacent partials were not equal and this resulted in a decreased uniformity of modulation rates across filters. The model proposed that the lower uniformity interferes with 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 thresholds similar to a harmonic masker provided that the modulation rates are uniform across the auditory filters involved in processing the masker and probe. Thus, the lowered threshold associated with a harmonic masker appears to arise from uniform modulation rates across auditory filters, and does not require periodicity in the fine structure of the waveform produced by partial frequencies that are 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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".