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Record W2965123398 · doi:10.2138/am-2019-6914

Transition metals in komatiitic olivine: Proxies for mantle composition, redox conditions, and sulfide mineralization potential

2019· article· en· W2965123398 on OpenAlexaboutno aff
Marek Locmelis, Ricardo Arévalo, Igor S. Puchtel, Marco L. Fiorentini, Euan Nisbet

Bibliographic record

VenueAmerican Mineralogist · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
FundersCentre of Excellence for Core to Crust Fluid Systems, Australian Research CouncilMacquarie UniversityNatural Environment Research CouncilSight Research UKMissouri University of Science and Technology
KeywordsOlivineGeologyGeochemistrySulfideMineral redox bufferMelt inclusionsMantle (geology)CratonSilicateSulfurMineralogyChemistryMaterials scienceMetallurgy

Abstract

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Abstract We present the results of a comprehensive study on the concentrations of first-row transition elements (FRTE: Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn), as well as Ga and Ge, in liquidus olivine from 2.7–3.5 Ga old Al-undepleted and Al-depleted komatiites from the Kaapvaal and Zimbabwe Cratons in southern Africa, the Yilgarn Craton in Australia, and the Superior Craton in Canada. The sample set includes komatiites that remained sulfur-undersaturated upon emplacement, as well as komatiites that reached sulfide saturation owing to assimilation of crustal sulfur. All olivine grains display concentrations of Mn, Zn, Ge, Co, Fe, Mg, and Ni similar to the Bulk Silicate Earth (BSE) values, with significant negative anomalies in Sc, Ti, V, Cr, Ga, and Cu. Olivine from the studied Al-depleted komatiites displays on average higher 100×Ga/Sc ratios (>5) than olivine from Al-undepleted komatiites (≤5). Because garnet preferentially incorporates Sc over Ga, the data suggest that elevated Ga/Sc ratios in komatiitic olivine are indicative of garnet retention in the source region of komatiites, highlighting the potential of olivine trace element chemistry as a proxy for the depth of komatiite melting and separation of the magma from the melting residue. Copper concentrations in the studied olivine grains are controlled by sulfur saturation of the host komatiite during olivine crystallization. Olivine from sulfur-undersaturated komatiite systems displays Cu concentrations mostly between 1 and 10 ppm, whereas olivine from sulfide-bearing komatiites has Cu contents of <0.5 ppm. Because komatiites contain some of the world's highest metal tenor magmatic Ni-Cu sulfide deposits, the Cu variability in olivine as a function of the sulfide-saturation state highlights a potential application of olivine chemistry in the exploration for sulfide ore deposits. Olivine from the Paleo-Archean (3.5–3.3 Ga) komatiites displays overall higher V/Sc ratios (V/Sc = 2.1 ± 0.96; 2 S.D.) than olivine from their Neo-Archean (2.7 Ga) counterparts (V/Sc = 1.0 ± 0.81, 2 S.D.). Vanadium and Sc behave similarly during partial melting of the mantle and are similarly compatible in majorite garnet. However, V is redox-sensitive and its compatibility in olivine increases as the system becomes less oxidized, whereas Sc is redox-insensitive. We argue that olivine from the studied Paleo-Archean komatiites crystallized from more reduced magmas than their Neo-Archean counterparts. Elevated Fe/Mn ratios in olivine from Paleo-Archean komatiites mimic the V/Sc signatures and are interpreted to reflect that Fe2+ is more compatible in olivine than Fe3+. These results imply that V/Sc and Fe/Mn in komatiitic olivine may potentially provide insight into the evolution of the oxidation state of the Archean mantle. Additional studies that integrate the chemistry of komatiitic olivine with those of relict interstitial glass and melt/fluid inclusions are encouraged to fully understand and quantify the potential of FRTE in olivine as a proxy for the oxidation state of the mantle sources of komatiite magmas.

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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 score0.065
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)0.0010.000

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 head0.005
GPT teacher head0.209
Teacher spread0.203 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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