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Record W4404840300 · doi:10.5382/econgeo.5104

Shape and Size Distribution of Sulfide Globules in the Raglan Magmatic Sulfide Deposit: Implications for Deposition and Exploration of Massive Sulfide Orebodies

2024· article· en· W4404840300 on OpenAlexaffabout
Ying Zhou Li, James E. Mungall

Bibliographic record

VenueEconomic Geology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsCarleton UniversityGovernment of Saskatchewan
Fundersnot available
KeywordsSulfideGeologyGeochemistryDeposition (geology)Volcanogenic massive sulfide ore depositMineralogyPyriteMetallurgyGeomorphologySedimentMaterials scienceSphalerite

Abstract

fetched live from OpenAlex

Abstract Globular sulfide is the best-preserved textural representation of immiscible sulfide liquids in silicate magmas, containing valuable information about the mechanisms of their transport and deposition and the formation of magmatic sulfide deposits. Previous studies have indicated that sulfide globule textures may convey useful information about their proximity to massive sulfide accumulations. This study quantitatively evaluates the genetic and spatial relationships between globular sulfides and massive orebodies in Zones 8 and 14 of the Raglan Horizon of northern Quebec by investigating their geochemical characteristics and systematically measuring globule size distributions (GSDs) across this portion of the Raglan deposit group. Their compositions suggest that sulfide globules, disseminated sulfides, net-textured sulfides, and massive sulfides in Zones 8 and 14 are genetically related and geochemically indistinguishable. The sulfide GSDs show that most samples taken from locations distal to massive lenses exhibit a simple log-linear relationship resembling the result of a single homogeneous nucleation event with linear growth and relatively constant nucleation density, or disaggregation of sulfide droplets by ligament stretching. In contrast, most samples of the proximal population show kinked GSD shapes. The kinked profiles can be attributed to processes possibly including mechanical sorting, Ostwald ripening, coalescence of sulfide globules, or the mixing of two globule populations with different size distributions. Whereas mechanical sorting, Ostwald ripening, and coalescence between sulfide globules are considered as, at most, minor contributors to the GSD shapes observed in this region, the kinked GSDs are best explained as representations of a mixed population of large, transported globules deposited in an early stage and finer-grained sulfide droplets deposited in a latter stage. Based on these interpretations, an ore-forming mechanism is proposed which starts with (1) deposition of large sulfide globules in a footwall embayment during turbulent magma flow in which the finer globules remain in suspension, followed by (2) the deposition and entrapment of fine-grained sulfide microdroplets due to a transition from turbulent to a transitional or laminar flow regime, and eventually (3) the rapid downward percolation of sulfide microdroplets through the pore network of the cumulate pile to form massive sulfide pools on the hard substrate of the footwall embayment. Furthermore, we find a close spatial relationship between samples with kinked GSDs and high globule number densities and massive sulfide ores. We demonstrate the robustness of using globule number density as a pointer to massive sulfide accumulations by successfully predicting the actual locations of orebodies 8M, 14K, and 14J in a 3-D space. Overall, we suggest that the texture of large globules immersed in finely dispersed clouds of abundant disseminated small sulfide globules is a strong indicator for proximity to massive sulfide accumulations, and the recognition of this texture may provide a critical tool for future exploration for massive magmatic sulfide ore lenses. We present schematic illustrations of favorable and unfavorable GSDs to aid in the qualitative application of these concepts during logging of exploration drill core.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.222
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes2
Has abstractyes

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