Bibliographic record
Abstract
The rapid flow of geothermally heated seawater through a complex subterranean hydrothermal system and the turbulent expulsion of the fluid into cold surrounding seawater at a vent are possible sources of underwater noise. Since their discovery in 1977, ambient sound-level anomalies have been documented near vent fields, spurring interest in the use of passive acoustics for monitoring of hydrothermal vent activity. This chapter summarizes the extant acoustic measurements of hydrothermal vents, including location, date, frequency range, and estimated source level. The acoustic source mechanisms anticipated at hydrothermal vents are explained theoretically, and examples of expected source levels for each mechanism are provided for realistic black smoker vent properties. Common confounding ambient sound sources are identified to assist in source discrimination. Finally, considerations for future acoustic measurements are provided, including discussion of the effects of flow noise and sensor proximity to the vent. Despite a relatively small number of measurements and inconclusive results to date with respect to monitoring of vent activity with passive acoustics, the theoretical source levels suggest this approach is feasible. Recommendations toward increasing the success of passive acoustic monitoring, such as the use of coherent processing of hydrophone arrays to aid in source identification, are provided.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".