The soundscape of two deep-sea hydrothermal vent sites
Bibliographic record
Abstract
Hydrothermal vents are sea floor structures where geothermally heated seawater is discharged. The high-temperature, chemically rich environment is host to uniquely adapted marine life. Vent soundscapes may contain important bioacoustic cues as well as signals enabling passive acoustic monitoring of hydrothermal vent dynamics. Proposals for deep-sea mining of seafloor massive sulfides near hydrothermal vents have elicited concern over potential environmental impacts due to disturbance from industrial activity, including changes to the soundscape. This study assesses the baseline soundscape at two sites, the Main Endeavour Field on the Juan de Fuca Ridge and the Lucky Strike vent field on the Mid-Atlantic Ridge over 12 months and 3 months respectively. To facilitate comparison with future studies at other sites, the most recently proposed standard soundscape analysis methodologies are employed, including terminology in alignment with ISO 18405:2017. In accordance with the latest soundscape standard literature, metrics quantifying the amplitude, impulsiveness, periodicity, and uniformity are reported. Spectral probability densities, percentiles, and long-term spectrograms are computed in hybrid millidecade frequency bands. Finally, a qualitative analysis is included to describe the source types contributing to the hydrothermal vent sound field.
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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 | 0.001 |
| 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 | 0.001 |
| 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".