Psychoacoustic Parameters and Ear Canal Role
Bibliographic record
Abstract
Background and objective(s): Effects of different parts of the human ear on the psychoacoustic parameters did not study before So, the purpose of this study was to see that the psychoacoustic parameters could change significantly in the effects of human ear canal and gender had an important role on it or not. Methods: White and sinusoidal noises were used at three levels, including 75, 85, and 95 dB as the stimulus sound pressure levels (SSPLs). The psychoacoustic parameters including loudness, sharpness, roughness and fluctuation strength were measured outside (cavum part of the external ear) and inside the right ear of each participant. The duration for each measurement was 10 seconds. Independent sample t-test and repeated measures ANOVA test were used for the statistical analysis, and the equality of means was rejected at p0.05). For both sinusoidal noise and the white noise in all three studied SSPLs the differences of four studied psychoacoustic parameters between outside and inside of participants ear are not statistically significant (all P values>0.05). Conclusion: It seems that human ear canal did not have any effects on the psychoacoustics parameters so we can say that ear canal does not have any roles in the noise induced annoyance.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".