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Record W2908958535 · doi:10.4095/300241

Iron-oxide and alkali-calcic alteration ore systems and their polymetallic IOA, IOCG, skarn, albitite-hosted U±Au±Co, and affiliated deposits: a short course series. Part 1: introduction

2017· report· en· W2908958535 on OpenAlexaffabout
Louise Corriveau

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsIron oxide copper gold ore depositsSkarnGeochemistryGeologyOre genesisMineralogyHydrothermal circulationSeismology

Abstract

fetched live from OpenAlex

Worldwide, iron oxide copper-gold (IOCG) deposits form world-class mining districts. In a single deposit, such as Olympic Dam, resources can reach 10 billion tons at 0.78% Cu, 0.25kg/t U3O8, 0.30g/t Au, 1.0g/t Ag. Rare-earth resources can also be significant. Systems that form IOCG deposits also host many other deposit types. This short course illustrates the metasomatic growth of polymetallic magmatic-hydrothermal iron-oxide and alkali±calcic alteration systems and the genetic linkages among their iron oxide-apatite (IOA), iron oxide copper-gold (IOCG) and affiliated deposit types, using the Great Bear magmatic zone (Northwest Territories, Canada) as a prime example. Complementary information are also sourced from the Central Mineral Belt of the Makkovik Province (Labrador), the Romanet Horst of the Labrador Trough (Quebec) and the Bondy gneiss complex of the Grenville province (Quebec) in Canada as well as from deposits worldwide. The Great Bear systems are differentially uplifted, tilted, transcurrent-faulted, and locally exhumed. They escaped orogenic metamorphism and pervasive deformation. Their former sedimentary covers are largely eroded and Quaternary glaciation left only a sporadic till cover. Consequently, outcrops are non-weathered, glacially polished and nearly continuous exposing in structural 3D the metasomatic growth of iron-oxide and alkali±calcic alteration ore systems from paleo-depth to paleo-surface. Within systems, metasomatism is pervasive and intense at regional to deposit scale. From paleo-depth to paleo-surface and away from heat sources (sub-volcanic intrusions), the diagnostic alteration facies prograde from: From depth to surface and away from heat sources, the diagnostic alteration facies prograde from: Facies 1 Na, transitional Na-Ca-Fe and skarn; Facies 2 high temperature Ca-Fe; Facies 3 high temperature K-Fe; Facies 4 transitional K and K-skarn; Facies 5 low temperature K-Fe (± low temperature Ca-Mg); and Facies 6 epithermal alteration. The prograde, retrograde, telescoped and cyclical metasomatic reaction paths lead to a regular series of deposit types with varied metal associations and mineralisation styles from paleo-depth to paleo-surface: Iron oxide-apatite (IOA) and their REE mineralised variants; Iron oxide copper-gold (IOCG) and low Cu, Co, Bi variants; Polymetallic potassic-skarns; Albitite-hosted U and Au-Co-U; Mo-Re and other affiliated deposits. Space-time relationships between metasomatism, magmatism, deformation and mineralisation constrain element addition and depletion in ore fluids from sources to deposits. They also record fluid pathways, sources of fluid rejuvenation, and heat sources across the ore-forming environments. The information is synthesised into an ore deposit model adaptable to the variety of fluid (and potential melt) sources, host rocks and compositions these ore systems have. New petrological mapping protocols, rock nomenclatures, chemical map methodologies, discriminant chemical diagrams, and geological vectors to mineralisation stem from these findings. They collectively unify the complex and disparate attributes of these ore systems into effective exploration concepts and provide a novel geoscience framework to explore Canada's prospective terrains for IOCG and affiliated deposits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.010

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.

Opus teacher head0.024
GPT teacher head0.259
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2017
Admission routes2
Has abstractyes

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