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Record W3037395531 · doi:10.5382/econgeo.4742

Magnetite Chemistry by LA-ICP-MS Records Sulfide Fractional Crystallization in Massive Nickel-Copper-Platinum Group Element Ores from the Norilsk-Talnakh Mining District (Siberia, Russia): Implications for Trace Element Partitioning into Magnetite

2020· article· en· W3037395531 on OpenAlexaffabout
Charley J. Duran, Sarah‐Jane Barnes, Eduardo T. Mansur, Sarah Dare, L. Paul Bédard, Sergey F. Sluzhenikin

Bibliographic record

VenueEconomic Geology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMagnetiteSulfideFractional crystallization (geology)SilicateGeologyGeochemistryCrystallizationHydrothermal circulationPlatinum groupSulfide mineralsTrace elementMineralogyChemistryMetallurgyMaterials sciencePlatinumCatalysis

Abstract

fetched live from OpenAlex

Abstract Mineralogical and chemical zonations observed in massive sulfide ores from Ni-Cu-platinum group element (PGE) deposits are commonly ascribed to the fractional crystallization of monosulfide solid solution (MSS) and intermediate solid solution (ISS) from sulfide liquid. Recent studies of classic examples of zoned orebodies at Sudbury and Voisey’s Bay (Canada) demonstrated that the chemistry of magnetite crystallized from sulfide liquid was varying in response to sulfide fractional crystallization. Other classic examples of zoned Ni-Cu-PGE sulfide deposits occur in the Norilsk-Talnakh mining district (Russia), yet magnetite in these orebodies has received little attention. In this contribution, we document the chemistry of magnetite in samples from Norilsk-Talnakh, spanning the classic range of sulfide composition, from Cu poor (MSS) to Cu rich (ISS). Based on textural features and mineral associations, four types of magnetite with distinct chemical composition are identified: (1) MSS magnetite, (2) ISS magnetite, (3) reactional magnetite (at the sulfide-silicate interface), and (4) hydrothermal magnetite (resulting from sulfide-fluid interaction). Compositional variability in lithophile and chalcophile elements records sulfide fractional crystallization across MSS and ISS magnetites and sulfide interaction with silicate minerals (reactional magnetite) and fluids (hydrothermal magnetite). Estimated partition coefficients for magnetite in sulfide systems are unlike those in silicate systems. In sulfide systems, all lithophile elements are compatible and chalcophile elements tend to be incompatible with magnetite, but in silicate systems some lithophile elements are incompatible and chalcophile elements are compatible with magnetite. Finally, comparison with magnetite data from other Ni-Cu-PGE sulfide deposits pinpoints that the nature of parental silicate magma, degree of sulfide evolution, cocrystallizing phases, and alteration conditions influence magnetite composition.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

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)0.0180.000

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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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.

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

Citations32
Published2020
Admission routes2
Has abstractyes

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