Distribution of Vapor and Condensate in a Hydrothermal System: Insights From Self‐Potential Inversion at Mount Tongariro, New Zealand
Bibliographic record
Abstract
Abstract Inversion of self‐potential data for source current density, js, in complex volcanic settings, yields hydrological information without the need for a prior groundwater flow model; js contains information about pH, pore saturation, and permeability, from which we infer the distribution of liquid and vapor phases. To understand the hydrothermal flow dynamics and hydraulic connectivity between surface thermal features at Mount Tongariro volcano, New Zealand, we undertook a reconnaissance scale self‐potential survey and developed an inversion routine for js, constrained by an existing 3‐D conductivity model from magnetotelluric measurements. The 3‐D distribution of js at Mount Tongariro reveals a discontinuous zero js zone interpreted as vapor or residually saturated pore space, surrounded by low to moderate js interpreted as circulating condensate liquid. Bounding faults act as conduits for down flowing groundwater or condensate, as well as barriers for the hydrothermal system. Localized small‐scale circulation associated with individual surface thermal features, rather than a single circulating system, accounts for the lack of widespread anomalous geochemical observations prior to the 2012 Te Maari eruption.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".