Komatiite-Associated Ni-Cu-(PGE) Deposits, Abitibi Greenstone Belt, Superior Province, Canada
Bibliographic record
Abstract
Magmatic sulfide deposits fall into two major groups when considered on the basis of the value of their contained metals, one group in which Ni, and, to a lesser extent, Cu, are the most valuable products and a second in which the PGE are the most important. The first group includes komatiite- (both Archean and Paleoproterozoic), flood basalt-, ferropicrite-, and anorthosite complex-related deposits, a miscellaneous group related to high Mg basalts, Sudbury, which is the only example related to a meteorite impact melt, and a group of hitherto uneconomic deposits related to Ural-Alaskan–type intrusions. PGE deposits are mostly related to large intrusions comprising both an early MgO- and SiO2-rich magma and a later Al2O3-rich, tholeiitic magma, although several other intrusive types contain PGE in lesser, mostly uneconomic quantities. Most Ni-rich deposits occur in rocks ranging from the Late Archean to the Mesozoic. PGE deposits tend to predominate in Late Archean to Paleoproterozoic intrusions, although the limited number of occurrences casts doubt on the statistical validity of this observation.A number of key events mark the development of a magmatic sulfide deposit, partial melting of the mantle, ascent into the crust, development of sulfide immisciblity as a result of crustal interaction, ascent of magma + sulfides to higher crustal levels, concentration of the sulfides, their enrichment through interaction with fresh magma (not always the case), cooling and crystallization. Factors governing this development include (1) the solubility of sulfur in silicate melts and how this varies as a function of partial mantle melting and subsequent fractional crystallization, (2) the partitioning of chalcophile metals between sulfide and silicate liquids, and how the results of this vary during mantle melting and subsequent crystallization and sulfide immiscibility (degree of melting and crystallization, R factor and subsequent enrichment), (3) how effectively the sulfides become concentrated and the factors controlling this, and (4) processes that occur during the cooling of the sulfide liquid that govern aspects of exploration and mineral beneficiation. These topics are discussed first in general terms and then with specific reference to deposits at Noril'sk, Kambalda, and Voisey's Bay. With regard to Voisey's Bay, quantitative modeling is consistent with the very low PGE concentrations in this deposit being the result of some sulfide having been left behind in the mantle during partial melting. Both the Noril'sk and Voisey's Bay deposits are shown to be economic because of subsequent upgrading of the
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".