Molecular evidence of shipping noise impact on the blue mussel, a key species for the sustainability of coastal marine environments
Bibliographic record
Abstract
Global anthropogenic oceanic noise caused by shipping is predicted to double every 11.5 yr, putting marine organisms at risk. While the impact of noise on marine mammals is well documented, its effects on molluscs, which hold immense economic and ecological importance, remain largely unknown. To investigate the consequences of noise on mollusc metabolism during crucial early life stages, blue mussel Mytilus edulis larvae were exposed to shipping noise in a laboratory setting until the post-larval stage and their metabolome was analysed. Multivariate analyses of the metabolome showed that shipping noise induced stress-related inflammation with increased energy demand, higher protein turnover, and disrupted nervous system activity. Consequently, noise promoted delayed metamorphosis in suboptimal habitats with greater metabolic costs, which may affect ecosystem and aquaculture sustainability as competent mussel larvae struggle to select suitable development habitats. Without action to limit underwater noise, such impacts could disrupt population structures and marine biodiversity.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".