Rethinking the Use of Seabed Sediment Temperature Profiles to Trace Submarine Groundwater Flow
Bibliographic record
Abstract
Abstract Submarine groundwater fluxes across the seafloor facilitate important hydrological and biogeochemical exchanges between oceans and seabed sediment, yet few studies have investigated spatially distributed groundwater fluxes in deep‐ocean environments such as continental slopes. Heat has been previously applied as a submarine groundwater tracer using an analytical solution to a heat flow equation assuming steady state conditions and homogeneous thermal conductivity. These assumptions are often violated in shallow seabeds due to ocean bottom temperature changes or sediment property variations. Here heat tracing analysis techniques recently developed for terrestrial settings are applied in concert to examine the influences of groundwater flow, ocean temperature changes, and seabed thermal conductivity variations on deep‐ocean sediment temperature profiles. Temperature observations from the sediment and bottom ocean water on the Scotian Slope off eastern Canada are used to demonstrate how simple thermal methods for tracing groundwater can be employed if more comprehensive techniques indicate that the simplifying assumptions are valid. The spatial distribution of the inferred groundwater fluxes on the slope suggests a downward groundwater flow system with recharge occurring over the upper‐middle slope and discharge on the lower slope. We speculate that the downward groundwater flow inferred on the Scotian Slope is due to density‐driven processes arising from underlying salt domes, in contrast with upward slope systems driven by geothermal convection. Improvements in the design of future submarine hydrogeological studies are proposed for thermal data collection and groundwater flow analysis, including new equations that quantify the minimum detectable flux magnitude for a given sensor accuracy and profile length.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 teacher head, 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".