Bibliographic record
Abstract
Transient acoustic signals were recently detected at the Main Endeavour Hydrothermal Vent Field which are believed to be generated by both geological and biological sources, including vent chimney collapse, impulsive geological signals, fish grunts, and snapping. These signals provide an opportunity for long-term passive acoustic monitoring of hydrothermal vent activity and ecology. This method offers advantages of longevity and robustness compared with other monitoring techniques, as the sensor can remain a safe distance away from the high-temperature, caustic vent fluid. Utilizing recordings from a bottom-mounted hydrophone on Ocean Networks Canada’s NEPTUNE observatory, a detector was implemented to identify and classify these signals in more than one year of acoustic data after 2016. While only a single hydrophone is available at this site, an array of three seismic accelerometers also on the NEPTUNE observatory was used to localize transient events when sufficient signal-to-noise ratio was available to provide confidence in the location estimate. Correlation of the transient sounds with seismic activity at the vent field was also evaluated, suggesting that passive acoustic monitoring can augment seismic records to provide additional information regarding geological activity at hydrothermal vent sites.
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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 | 0.000 |
| 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".