How chronic anthropogenic noise can affect wildlife communities
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
Anthropogenic noise is a major pollutant in terrestrial and aquatic ecosystems. Since the industrial revolution, human activities have become increasingly noisy, leading to both acute and chronic disturbance of a wide variety of animals. Chronic noise exposure can affect animals over their lifespan, leading to changes in species interactions and likely altering communities. However, the community-level impacts of chronic noise are not well-understood, which impairs our ability for effective mitigation. In this review, we address the effects of chronic noise exposure on communities and explore possible mechanisms underlying these effects. The limited studies on this topic suggest that noise can affect communities by changing the behavior and/or physiology of species in a community, which results in direct or knock-on consequences for other species in the ecosystem. Major knowledge gaps remain due to the logistically complex and financially expensive nature of the long-term studies needed to address these questions. By identifying these gaps and suggesting approaches to answer them, we provide a road map toward mitigating the effects of a noisy world.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 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 it