Sulfur isotope compositions in the weathering profile of magmatic Ni-Cu deposits in SW Australia
Bibliographic record
Abstract
The Nova-Bollinger Ni-Cu sulfide ore deposit is hosted in layered mafic and ultramafic intrusive rocks of the Mesoproterozoic Albany-Fraser zone, located about 160 km east-northeast of Norseman, Western Australia. Nova and Bollinger are two adjacent but spatially distinct orebodies with a combined pre-mining resource estimate of 13.1 million tonnes (Mt) with about 2 % Ni, 0.8 % Cu, and 0.1 % Co (IGO Ltd., unpublished data, 2018) 1. Significant challenges are posed in exploring for magmatic Ni-Cu deposits that are buried under post-mineral cover. For example, electromagnetic and gravity surveys identify numerous targets but are unable to distinguish economic mineralization. Previously, it was suggested that the regular pattern of S isotope compositions (δ34SCDT) of surficial sulfate in lakes and groundwaters in southern Australia provides an ideal baseline against which to search for anomalous δ34SCDT values associated with base-metal or gold mineralization 2. In the absence of lakes and readily accessible groundwaters in prospective areas, soils and rocks make a convenient sampling medium. Here, we investigated the exploration potential of δ34SCDT of the trace sulfur content of unconsolidated surface sediments, saprolite, and bedrock samples above Nova and two nearby sub-economic prospects, Griffin and Chimera. The δ34SCDT values likely reflect a two end-member system, with values ranging from -5.8 at depth to 21.4 ‰ near the surface, showing little dependence on lithology. Values in samples closer to the surface are similar to modern seawater sulfate that has a globally homogenous δ34SCDT value of 21.0 ± 0.2 ‰ 3, whereas at depth, values approach typical mantle S isotopic compositions of 0 ± 2 ‰ 4. In support of this, rocks at Nova have a δ34SCDT of around 0 ‰ and regional metagabbro are between -2 and 4 ‰ 5. On a regional scale, in both Western Australia (Yilgarn Block) and South Australia, the δ34SCDT values of surficial gypsum have a regular pattern over distances of up to 1000 km, with the highest values (~ 21 ‰) near coastlines decreasing to δ34SCDT values of ~ 14 ‰ further inland 2. This is suggested to be predominantly the result of the delivery of salts to the Australian landscape as aerosols, with volatile biogenic S compounds of mostly marine origin (δ34SCDT of ~ 1 ‰) that proportionately increase in importance further inland resulting in decreasing δ34SCDT values 2. Located approximately 200 km inland, δ34SCDT results in samples within 10 metres of the surface at Nova, Griffin, and Chimera are in agreement with this and range from 12.6 to 20.4 ‰. Given that near-surface δ34SCDT values above Nova, Griffin, and Chimera appear to be mostly related to seawater-derived sulfate with minimal magmatic influence, δ34SCDT shows little potential as a field sampling technique to vector for deposits buried under post-mineral cover. However, at depth, δ34SCDT shows a clear relationship between the mixing of seawater sulfate and magmatic S weathering into the environment, indicating that analysis of S isotopes of otherwise apparently barren cores has utility in mineral exploration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".