Geo-Electrical Responses Associated with Hydrothermal Fluid Circulation in Oceanic Crust: Feasibility of Magnetometric and Electrical Resistivity Methods in Mapping Off-Axis Convection Cells
Bibliographic record
Abstract
Recent developments in theory and instrumentation have led to increasing interest in the use of geo-electrical techniques to map seafloor structure and to explore mineral deposits. Electrical experiments conducted at sea are difficult and costly to perform, reinforcing the need for theoretical design studies before any seagoing programs get underway.I present in this paper the first theoretical investigation of geoelectrical responses associated with hydrothermal fluid circulation in a mid-ocean ridge flank environment. A 2D conceptual electrical model is constructed based on hydrothermal modelling results, and its responses to two major ‘galvanic’ techniques (magnetometric resistivity (MMR) and electrical resistivity methods) are calculated using a finite difference computer package. Forward modelling results reveal that the marine MMR method is capable of detecting off-axis hydrothermal convection cells with equivalent or even greater resolution than traditional seafloor heat flow surveys. However, the electrical resistivity method is not applicable because this system suffers a very severe ‘shorting effect’ of the overlying seawater layer, which almost totally masks the contribution from the underlying oceanic crust.
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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 | 0.000 | 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".