Computing geochemical mass transfer and water/rock ratios in submarine hydrothermal systems: implications for estimating the vigour of convection
Bibliographic record
Abstract
Abstract A method of calculating chemical water/rock ratios is presented that enables the estimation of fluid velocities in open, flow‐through hydrologic systems. The approach is based on relating the gain/loss of a chemical species per kilogram of solid phase to the loss/gain of that species in the fluid phase, integrated across a specified length of the flowpath. After examining the underlying approximations of the approach using a one‐dimensional model of seawater moving through a basalt under nonisothermal conditions, the method is applied to representative zones within a two‐dimensional hydrothermal convective system. The method requires that regions within the flow system can be identified in which the direction of flow is steady for an extended period of time. Estimates of fluid velocity are spatial and temporal averages for the length of the flowpath used in the calculation. The location within the flow system and the nature of the alteration reactions determine which species can provide reliable values of the chemical water/rock ratio and useful estimates of fluid velocities. Over the length of the flowpath considered, the calculation of water/rock ratios works best when a species is controlled by a single reaction. Accurate estimates are favoured if the concentration profile of a species along the flowpath increases or decreases monotonically. If the length of the flowpath extends over more than one reaction zone, then erroneous estimates of the water/rock ratio and fluid velocity are more likely. Model calculations suggest that the quartz/silica system should provide reliable estimates for fluid velocity under a wide range of temperature and flow conditions, in particular in those regions of a system at or near quartz equilibrium, so that the aqueous silica concentration is buffered by quartz and correlated with the temperature distribution.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".