Microbubbles as Proxies for Oil Spill Delineation in Field Tests
Bibliographic record
Abstract
To overcome the environmental impacts of releasing oil into the ocean for testing acoustic methods in field experiments using autonomous underwater vehicles (AUVs), environmentally friendly gas bubble plumes with low rise velocities are proposed in this research to be used as proxies for oil. An experiment was conducted to test the performance of a centrifugal-type microbubble generator in generating microbubble plumes and their practicability to be used in field experiments. Sizes of bubbles were measured with a Laser In-Situ Scattering and Transmissometry sensor. Residence time of bubble plumes was estimated by using a Ping360 sonar. Results from the experiment showed that a larger number of small bubbles were found in deeper water as larger bubbles rose quickly to the surface without staying in the water column. The residence time of the generated bubble plumes at the depth of 0.5 m was estimated to be over 5 min. The microbubble generator is planned to be applied in future field experiments, as it is effective in producing relatively long-endurance plumes that can be used as potential proxies for oil plumes in field trials of AUVs for delineating oil spills.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".