How greisenization could trigger the formation of large vein-and-greisen Sn-W deposits: A numerical investigation applied to the Panasqueira deposit
Bibliographic record
Abstract
The formation of large tin-tungsten (Sn-W) deposits around granitic intrusions requires the circulation of large volumes of fluids within permeable structures. Half of the world’s tungsten production originates from highly mineralized veins above granitic intrusions and from the altered part of the granite (the greisen), whose formation results from intense fluid-rock interactions. During greisenization processes, mineral reactions involve a decrease in the rock volume and thus an increase in porosity and permeability. To understand the complex fluid-rock interactions leading to the formation of large Sn-W ore deposits, we conducted numerical modeling accounting for magmatic fluid production and realistic permeability changes due to granite alteration and overpressure in the hosting rocks. The water/rock ratio is computed to constrain the rate of greisenization and therefore the porosity and permeability evolution laws. Four model results are presented: with and without fluid production exsolved from the granitic magma, and with and without dynamic reaction-enhanced permeability. The formation of greisen is reproduced, and greisen thickness reaches 200 m for the more sophisticated model. The interplay between greisenization and fluid production creates zones of overpressure above the granite that could localize the permeable structures such as the veins swarm observed at Panasqueira. Dynamic permeability promotes high fluid velocity and intense fluid-rock exchanges that could result in the formation of large ore deposits by enhancing mass transfer within and above granitic intrusions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".