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Record W3104919996 · doi:10.5382/econgeo.4775

UPGRADING OF MAGMATIC SULFIDES, REVISITED

2020· article· en· W3104919996 on OpenAlexaff
James E. Mungall, M. Christopher Jenkins, Samuel J. Robb, Zhuosen Yao, James M. Brenan

Bibliographic record

VenueEconomic Geology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsDalhousie UniversityCarleton University
Fundersnot available
KeywordsSulfideSilicateMineralization (soil science)GeochemistryGeologyPlatinum groupSulfide mineralsChemistryPyriteCatalysisPlatinumSoil science

Abstract

fetched live from OpenAlex

Abstract There has been vigorous debate for several decades about whether the extreme enrichments of platinum group elements (PGEs) in some magmatic sulfide deposits could have resulted from simple equilibration of sulfide liquid with silicate melt. Key examples include the Ni-Cu-Pd mineralization in the Norilsk mining camp, the UG2 and Merensky reef Pt-Pd deposits in the Bushveld Complex, the Pd-rich J-M reef of the Stillwater Complex, and the Skaergaard Pd-Au mineralization. It was argued historically that the observed PGE tenors in these latter deposits are too high to be consistent with simple equilibration of sulfide and silicate melt. A commonly cited mechanism for increasing PGE tenor in magmatic sulfide is the upgrading of initially low tenor sulfide by allowing a small volume of sulfide to react with successive batches of fresh, previously undepleted silicate magma. Here we review several previous models for sulfide upgrading in light of recent changes in accepted values of the partition coefficients governing PGE exchange between sulfide and silicate, and we critically examine the physical scenarios implicit in each previous model. We show that, although sulfide upgrading may occur in natural settings such as fractional melting of the mantle, during the formation of sulfide accumulations from magmas it is unlikely to have effects that can be distinguished from simple one-stage batch equilibration. Even the most PGE-rich deposits currently known have compositions that can easily be accounted for by the simple one-stage batch process, with the possible exception of the Skaergaard Pd mineralization. It is generally not possible to use the measured composition of accumulations of magmatic sulfide to infer that sulfide upgrading has or has not occurred.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.999

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)0.0530.002

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 head0.183
Teacher spread0.169 · 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; both teacher heads agree on what is shown here.

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

Citations28
Published2020
Admission routes1
Has abstractyes

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