Fertility of Gabbroic Intrusions in the Paleoproterozoic Lynn Lake Greenstone Belt, Manitoba, Canada: Insights from Field Relationships, Geochemical and Metallogenic Characteristics
Bibliographic record
Abstract
Magmatic nickel–copper–platinum group element (PGE) deposits hosted in mafic–ultramafic intrusions within volcanic arc systems are highly attractive targets for mineral exploration, yet their genesis remains poorly understood. This study investigates metagabbroic intrusions in the Paleoproterozoic Lynn Lake greenstone belt of the Trans-Hudson Orogen to identify the key factors, in the original gabbros, that control the formation of magmatic Ni-Cu-PGE deposits in volcanic arc systems. By examining the field relationships, geochemical and sulfur and oxygen stable isotope compositions, mineralogy, and structural fabrics, this study aims to explain why some intrusions host mineralization (e.g., Lynn Lake and Fraser Lake intrusions), whereas others remain barren (e.g., Ralph Lake, Cartwright Lake, and Snake Lake intrusions). Although both the fertile and barren gabbroic, likewise original, intrusions exhibit metaluminous, tholeiitic to calc-alkaline affinity with volcanic arc geochemical signatures, they differ significantly in shape, ranging from vertical and tube-like to tabular forms, reflecting distinct geological settings and magma dynamics. The gabbroic rocks of fertile intrusions exhibit erratic trace element profiles, lower (Nb/Th)N and higher (Cu/Zr)N ratios, as well as a larger range of δ34S values than those in barren intrusions. Key factors influencing Ni-Cu-PGE mineralization include the degree of partial melting of the mantle, early sulfide segregation, and crustal contamination, particularly from volcanogenic massive sulfide deposits. These processes likely triggered sulfide saturation in the mafic magmas. Geochemical proxies, such as PGE concentrations and sulfur and oxygen stable isotopes, provide critical insights into these controlling factors. The results of this study enhance our understanding of the metallogenic processes responsible for the formation of magmatic Ni-Cu-PGE deposits in the gabbroic intrusions emplaced in an extensional setting due to slab rollback, during the geological evolution of the Lynn Lake greenstone belt, offering valuable guidance for mineral exploration efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".