Marine electromagnetic imaging and volumetric estimation of large-scale freshwater plumes offshore Hawai'i
Bibliographic record
Abstract
Submarine groundwater discharge (SGD) is a flow of cold and buoyant freshwater from the seafloor the ocean surface. Because SGD contains carbon, nutrients, metals, and green-house gases, it changes the oceanographical and biochemical properties of coastal waters. Therefore, SGD is an important phenomenon that governs hydrological cycles at the land-to-ocean transition zone. Due to the high spatial distribution and variability of SGD at the ocean surface, it is nontrivial to map SGD seep location and fluxes using traditional oceanographic methods. Here, we present electromagnetic imaging of large freshwater plumes in high-resolution, offshore west of Hawai‘i island. Our electrical resistivity models detect multiple vertical freshwater plumes (SGD point-sources) as well as spatially distributed surface freshwater, extending to a distance of ~3 km offshore Hawai‘i. Plume-scale salinity distribution indicates that these plumes contain up to 87% of freshwater. Thus, a substantial volume of freshwater occupies Hawaiian water column plumes. Our findings provide valuable information to elucidate hydrogeologic and oceanographic processes affecting biogeochemical cycles in coastal waters worldwide. This is the first study to demonstrate the marine electromagnetic method’s capability to image and delineate freshwater plumes from the seafloor to the ocean surface. Keywords: Freshwater Plumes, SGD, Hawai'i, Surface-towed CSEM, high-resolution 2D electrical imaging.
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 | 0.000 |
| 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) | 0.000 | 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".