Long-term, quantitative observations of seafloor hydrothermal venting using an imaging sonar
Bibliographic record
Abstract
While connected to the NEPTUNE observatory operated by Ocean Networks Canada (ONC) at the Endeavour Segment of the Juan de Fuca Ridge (http://www.oceannetworks.ca/observatories/pacific), the Cabled Observatory Vent Imaging Sonar (COVIS) recorded an unprecedented long-term (>4 years) acoustic dataset capturing local hydrothermal venting. Processing of the acoustic backscatter data yields three-dimensional (3-D) images of plumes rising tens of meters from black smoker vents on a sulfide structure named Grotto. More importantly, analysis of the Doppler frequency shift in acoustic backscatter yields estimates of the flow rates of those plumes and their volume fluxes. Subsequent calculations based on the vertical variation in volume flux and a theoretical heat-to-volume-flux relationship for buoyancy-driven plumes give estimates of plume heat flux, which are essential for studying the temporal evolution of a hydrothermal system and its coupling with geological, oceanic, and biological processes. In addition to black-smoker plume observations, the ping-to-ping decorrelation of seafloor backscatter recorded by COVIS provides an acoustic indicator of diffuse-flow (i.e., low- temperature, clear hydrothermal discharge) distribution over Grotto and its surrounding areas. Furthermore, acoustic techniques for quantifying the temperature fluctuations, and ultimately, heat flux of diffuse-flow venting are currently under development. [Work supported by NSF.]
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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".