On the role of buoyancy force in the ore genesis of SEDEX deposits: Example from Northern Australia
Bibliographic record
Abstract
Finite element modeling on a highly conceptualized 2-D model of fluid flow and heat transport is un-dertaken to simulate the paleo-hydrological system as if the Mount Isa deposits were being formed in the Mount Isa basin, Northern Australia, and to evaluate the potential of buoyancy force in driving ba-sin-scale fluid flow for the formation of sedimentary-exhalative (SEDEX) deposits. Our numerical case studies indicate that buoyancy-driven fluid flow is controlled mainly by the fault penetration depth and its spatial relation with the aquifer. Marine water recharges the basin via one fault and flows through the aquifer where it is heated from below. The heated metalliferous fluid discharges to the basin floor via the other fault. The venting fluid temperatures are computed to be in the range of 115 to 160℃, with fluid velocities of 2.6 to 4.1 m/year over a period of 1 Ma. These conditions are suitable for the formation of a Mount Isa-sized zinc deposit, provided a suitable chemical trap environment is present. Buoyancy force is therefore a viable driving mechanism for basin-scale ore-forming hydrothermal fluid migration, and it is strong enough to lead to the genesis of supergiant SEDEX deposits like the Mount Isa deposit, Northern Australia.
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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) | 0.001 | 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".