Trace elements in Fe-oxide minerals from fertile and barren igneous complexes: investigating their use as a vectoring tool for Ni-Cu-PGE sulphide mineralization
Bibliographic record
Abstract
The aim of this study was to develop a new technique to determine the fertility of mafic intrusions for Ni-Cu-PGE sulphide mineralization using the mineral chemistry of Fe oxides in the silicate host rocks. A suite of 25 trace elements was determined in magnetite and ilmenite, by laser ablation ICP-MS at LabMaTer (UQAC), from a variety of barren and fertile igneous complexes. Two of Canadamp;gt;'s largest Ni deposits, the 1.85 Ga Sudbury Igneous Complex and its vast Ni-Cu-PGE mineral district (Ontario) and the 1.34 Ga Eastern Deeps Intrusion-hosting Ni-Cu-Co sulphide mineralization at Voiseymp;gt;'s Bay (Newfoundland), were selected for study. Samples chosen from igneous complexes that are barren of significant Ni sulphide mineralization comprise layered mafic intrusions (Bushveld Complex, South Africa and Sept Iles, Quebec) and anorthosite suites (Saguenay-Lac-St.-Jean, Quebec) that host Fe-Ti-V-P oxide deposits, some of which contain trace amounts of Ni-Cu-PGE sulphides. Mafic rocks of the 1.33 Ga Newark Island layered intrusion (Labrador) were also studied as they are similar in composition and setting to Voisey's Bay but devoid of significant Ni sulphide mineralization. In sulphide-undersaturated magmas, Cu, Sn, Mo, and Zn are incompatible during fractionation and thus increase in concentration in late-crystallizing magnetite and ilmenite. Upon sulphide saturation and the formation of a trace amount of sulphide, only Cu is depleted in the silicate magma relative to the incompatible elements. Copper depletion, as recorded by Fe oxides, is a sensitive indicator of sulphide saturation and can be diagnostic of whether a Ni-bearing sulphide deposit will have formed if the Cu depletion occurred early during fractionation. In contrast, Ni and Co are compatible during fractionation, partitioning into olivine, orthopyroxene, and, where present, sulphide, and their concentrations steadily decrease in the Fe oxides, together with Cr, as crystallization proceeds. Iron oxides from barren igneous complexes plot on a single Ni-Cr trend but Fe oxides from fertile complexes (those hosting Ni sulphide deposits) plot on a parallel Ni-Cr trend displaced to lower Ni concentration. Nickel depletion is therefore recorded in Fe oxides and has the potential to identify intrusions with buried Ni-sulphide mineralization. The advantages of using Fe oxides as an exploration tool include their resistance to post-magmatic processes, such as alteration, and their preservation and easy recovery from glacial till and heavy mineral separates.
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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) | 0.000 | 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 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".