Perceived Loudness Sensitivity Influenced by Brightness in Urban Forests: A Comparison When Eyes Were Opened and Closed
Bibliographic record
Abstract
Soundscape plays a positive, health-related role in urban forests, and there is a competitive allocation of cognitive resources between soundscapes and lightscapes. This study aimed to explore the relationship between perceived loudness sensitivity and brightness in urban forests through eye opening and closure. Questionnaires and measuring equipment were used to gather soundscape and lightscape information at 44 observation sites in urban forested areas. Diurnal variations, Pearson’s correlations, and formula derivations were then used to analyze the relationship between perception sensitivity and how perceived loudness sensitivity was influenced by lightscape. Our results suggested that soundscape variation plays a role in audio–visual perception in urban forests. Our findings also showed a gap in perception sensitivity between loudness and brightness, which conducted two opposite conditions bounded by 1.24 dBA. Furthermore, we found that the effect of brightness on perceived loudness sensitivity was limited if variations of brightness were sequential and weak. This can facilitate the understanding of individual perception to soundscape and lightscape in urban forests when proposing suitable design plans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".