On the Relationship Between Alteration Facies and Metal Endowment of Iron Oxide-Alkali-Altered Systems, Southern Great Bear Magmatic Zone (Canada)
Bibliographic record
Abstract
The Great Bear magmatic zone in northern Canada hosts large iron oxide and alkali-altered systems that developed within a 10-m.y. period during the Paleoproterozoic. In the Eastern Treasure Lake and Duke sectors, and at the NICO deposit, early albitization associated with magmatism was followed by tungsten mineralization that was spatially associated with extensive skarn and Fe skarn alteration. Subsequent fluid-rock reactions led to substantial iron enrichment that culminated in iron oxide-apatite mineralization. At the transition from compressional/transpressional to extensional/transtensional stress regimes, changes in magma composition increased the metal budget of exsolved magmatic-hydrothermal fluids and played a key role in the formation of Au-Co-Bi mineralization at the NICO deposit and its satellite showings in the Duke zone. This process happened as the systems regionally transitioned to magnetite-bearing, potassic-iron alteration. The continued evolution of magmatism and fluid chemistry then contributed to the formation of iron oxide-copper-gold (IOCG) and variant mineralized zones in the Sue-Dianne and NICO deposits and other showings, and albite-hosted uranium mineralized zones elsewhere. The Great Bear magmatic zone illustrates that the evolution of magmatically derived fluids during a transition between different stress regimes can play a significant role in metal endowment and the ability of metasomatic systems to form skarn, iron oxide-apatite, IOCG, and albitite-hosted uranium mineralization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".