A synthesis of health benefits of natural sounds and their distribution in national parks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
= 1.63, 95% CI = 0.09, 3.16). Examples of beneficial outcomes include decreased pain, lower stress, improved mood, and enhanced cognitive performance. Given this evidence, and to facilitate incorporating public health in US national park soundscape management, we then examined the distribution of natural sounds in relation to anthropogenic sound at 221 sites across 68 parks. National park soundscapes with little anthropogenic sound and abundant natural sounds occurred at 11.3% of the sites. Parks with high visitation and urban park sites had more anthropogenic sound, yet natural sounds associated with health benefits also were frequent. These included animal sounds (audible for a mean of 59.3% of the time, SD: 23.8) and sounds from wind and water (mean: 19.2%, SD: 14.8). Urban and other parks that are extensively visited offer important opportunities to experience natural sounds and are significant targets for soundscape conservation to bolster health for visitors. Our results assert that natural sounds provide important ecosystem services, and parks can bolster public health by highlighting and conserving natural soundscapes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it