The association of noise sensitivity with musical aptitude and everyday use of music
Bibliographic record
Abstract
We aimed to study if noise sensitivity is associated with musical aptitude and everyday use of music. A total of 197 participants was recruited in Finland (N=91; 44 men, 47 women) and in Italy (N=106; 10 men, 96 women). The age range was from 19 to 56 years. We administered questionnaires and listening tests both online and in laboratory. Noise sensitivity was studied using the Weinstein's Noise Sensitivity Scale. Musical aptitude was tested with Seashore tests for Pitch and Time and Montreal Battery of Evaluation Amusia (MBEA). The correlation test did not show significant relationship between noise sensitivity and performance in Seashore test for Time. The correlation between noise sensitivity and the results on Pitch subscale was marginally significant indicating that subjects with lower noise sensitivity tend to perform better on pitch discrimination task. No significant correlations were found between noise sensitivity and MBEA scores. Noise sensitivity was negatively correlated with the amount of passive music listening meaning that subjects with higher noise sensitivity use music as a background more seldom than subjects with lower noise sensitivity. No association was found between noise sensitivity and the amount of active music listening a week.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".