Bibliographic record
Abstract
The presence of noise is a salient cue to the perception of breathiness and aspiration in speech sounds. The detection of noise within harmonic series (maskers) composed of unresolved components was found to depend on the fundamental frequency (fo) and the overall level of the masker [Gockel, Moore, and Patterson (2002). J. Acoust. Soc. Am., 111 (6), 2759–2770]. In the present study, noise detection thresholds were measured as a function of the frequency range, the fo, and the overall level of harmonic maskers. Frequency range was specified in equivalent rectangular bandwidth (ERB) units (3–13, 13–23, 23–33, or 3–33 ERBs). The results were consistent with the idea that listeners rely on spectral cues when maskers comprise only resolved components (3–13 ERBs), and on temporal (dip listening) cues when maskers contain only unresolved components (23–33 ERBs). Noise detection thresholds were generally lower when masker level was high (70 dBA) than when it was low (50 dBA). Masker fo affected thresholds only when listeners relied on spectral cues for noise detection. With the wideband (3–33 ERBs) masker, listeners likely detected noise by focusing on the frequency band (23–33 ERBs) with the most advantageous noise-to-harmonic ratio.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| 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".