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Record W4392589602 · doi:10.5194/egusphere-egu24-805

Links between volcanogenic massive sulfide endowment and volcanic rock geochemistry: comparing two assemblages from the Archean Abitibi greenstone belt, Canada

2024· preprint· en· W4392589602 on OpenAlexaffabout
Octavio Vite-Sánchez, Pierre‐Simon Ross, P Mercier-Langevin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsGeological Survey of CanadaInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsArcheanGreenstone beltGeologyGeochemistryVolcanoVolcanogenic massive sulfide ore depositVolcanic rockEndowmentSulfidePetrologySphaleriteChemistryPyrite

Abstract

fetched live from OpenAlex

Volcanogenic massive sulfide (VMS) deposits exhibit stratigraphic and structural controls at the district scale. However, the factors contributing to the varying fertility of volcanic centers, assemblages, or entire greenstone belts remain unclear. Notably, in the Archean Abitibi greenstone belt (Canada), the Stoughton-Roquemaure (S-R) assemblage accounts for <1% of VMS tonnage of the belt, while the much less voluminous Blake River (BR) assemblage hosts almost half of the VMS tonnage. To compare the two assemblages and assess potential petrogenetic controls on VMS fertility, a compilation and filtering of whole-rock geochemistry (n = 4541 samples) has been completed. To explore the dataset, multivariate methods, such as Principal Component Analysis, were utilized. A Th/Yb versus Zr/Ti diagram was developed, on which twelve geochemical clusters were identified. The clusters range from mafic to felsic and from tholeiitic to calc-alkaline. Additionally, the study includes an examination of two ultramafic compositions—komatiitic basalts and komatiites. The Magma Chamber Simulator (MCS) was employed to model fractional crystallization (FC), assimilation-fractional crystallization (AFC), and magma mixing as possible petrogenetic processes for the formation of S-R and BR volcanic rocks. Several initial magma compositions ranging from ultramafic to mafic were evaluated, including different pressures, oxygen fugacities and water contents. Despite the presence of twelve geochemical groups, only two, tholeiitic basalts and high-Th basalts, accounts for almost half of the dataset (46%). Tholeiitic basalts, charachterized by low Th/Yb ratios (<0.2) and flat REE patterns are typically associated with extensional geodynamic contexts or large igneous provinces in the Phanerozoic. Contrastingly, high-Th basalts with high Th/Yb ratios (>0.5), LREE enrichments and transitional to calc-alkaline magmatic affinities are typically associated with continental/island arc environments in the Phanerozoic. In the Abitibi belt, tholeiitic basalts and high-Th basalts are however often intimately intercalated, at odds with modern tectonic environments. Our modeling suggests that magmas with moderate to high Th/Yb ratios and transitional to calc-alkaline signatures may result from a tholeiitic magma assimilating a TTG-like wall rock in the middle crust, explaining the association between the two types of rocks. Upon closer examination of predominantly volcanic geological formations hosting VMS, mafic to intermediate compositions mostly features moderate to high Th/Yb geochemical groups. However, not all successions with these characteristics are fertile. Felsic compositions occurring in the BR and S-R assemblages mostly feature (>90%) volcanic rocks with moderate to high Th/Yb ratios (>0.2-10). However, groups closely related to VMS activity feature moderate Th/Yb ratios (0.2-1) and are more abundant in the well-endowed BR. The petrogenetic models presented improve our understanding of Archean greenstone belt petrogenesis, and ongoing work will help further comprehend controls on VMS fertility.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.240
Teacher spread0.217 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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