Controls on the metal tenors of sulfide ores in the Jinchuan Ni–Cu–PGE sulfide deposit, NW China: Implications for the formation of distinct textural types of sulfide ores in magma conduits
Bibliographic record
Abstract
The giant Jinchuan Ni–Cu–platinum-group element (PGE) sulfide deposit is a magma conduit system comprising four main intrusive units termed segments III, I, II-W, and II-E. The deposit comprises disseminated, net-textured, massive sulfide, and Cu-rich sulfide ores, with variations in metal tenors occurring among these different ore types and among the segments. Controls on these metal tenor variations must be linked to metallogenic processes, but this remains poorly constrained. To asses this, we systematically compared metal tenors (Ni, Cu, and the PGE) of ores from two perspectives — i) different ore types in each segment and ii) a single ore type across all four segments. Two major styles of metal tenor variations are documented. Style 1: Segments III and I have higher metal tenors than segments II-W and II-E for any given type of ore. Based on sulfide segregation models, this variation is interpreted to be related to variable degrees of early removal of sulfide liquid from the magmas that formed the four segments. Style 2: Disseminated ores in segments III and I have higher metal tenors than the other ore types, whereas all of the ore types in segments II-W and II-E have similar metal tenors. This is interpreted to be the result of the disseminated ores in segments III and I having formed from sulfide liquids that experienced higher R factors than the sulfide liquids that formed the other ore types, whereas all of the ores in segments II-W and II-E formed from sulfide liquids that experienced similar R factors. This difference suggests that the different ore types in segments III and I formed via early percolation and accumulation of sulfide liquids (the net-textured and massive ores) followed by the capture of disseminated, high R factor sulfides (the disseminated ore), whereas the different ore types in segments II-W and II-E likely formed by the physical percolation of originally disseminated sulfide liquid through the inter-crystal pore space. This study demonstrates that both sulfide ore texture and their metal-tenor variations are critical to characterizing ore-forming processes in dynamic magma conduits.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".