Whole rock lithogeochemical analysis of the Mount Read Volcanics: a new tool for geochemical exploration
Bibliographic record
Abstract
The Mount Read Volcanics (MRV) of western Tasmania is a belt of Middle to Late Cambrian submarine volcanics and volcaniclastics and one of the major base and precious metal provinces within Australia. Exploration success in the MRV has been in decline in recent years due to a variety of challenges including intensely altered rocks with complex stratigraphy and lithofacies variation, and a lack of accessible outcrop. As a result, local and regional mapping of the MRV is often restricted to Group-level stratigraphy, rendering geological mapping ineffective for identifying decametre-scale mine stratigraphy. Surface rock chip and drill hole samples were collected and analysed using commercially available geochemical assays to create a regional geochemical dataset of the MRV, covering the entire province and all major stratigraphic units. From these data, a lithogeochemical methodology was developed, utilizing Ti/Nb and V/Sc systematics that effectively characterizes the samples according to composition and magmatic processes. This method is shown to be robust to biases due to alteration and lithofacies, eliminating the need for highly selective sampling or extensive data filtering. To demonstrate the utility of this method in an exploration context, data from the K-lens of the Rosebery polymetallic volcanic-hosted massive sulfide (VHMS) deposit was used as a case study. Using Ti/Nb–V/Sc systematics, a rock composition classification was developed that allowed for discrimination of the footwall, hanging wall and host stratigraphy of the Rosebery mine sequence. A geochemical fingerprint for the footwall stratigraphy to mineralization was developed, and by correlating this signature to the regional unclassified samples, geochemical analogues for the Rosebery footwall were readily identified. This approach rapidly reduces the exploration search space and provides valuable information for future mineral exploration. The methodology is applicable in other terrains; however, appropriate orientation studies are required to investigate potential biases due to lithofacies, alteration and mineralogical variability.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".