Zinc on the edge—isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits
Bibliographic record
Abstract
Abstract The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ ( 238 U/ 204 Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".