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Record W2160399220 · doi:10.2113/gsecongeo.96.3.645

EXTREME FRACTIONATION OF PLATINUM GROUP ELEMENTS IN VOLCANOGENIC MASSIVE SULFIDE DEPOSITS

2001· article· en· W2160399220 on OpenAlexaffabout
Yuanming Pan, Qianli Xie

Bibliographic record

VenueEconomic Geology · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPlatinum groupSulfideGeologyGeochemistryGroup (periodic table)PlatinumFractionationMineralogyChemistryMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Research Article| May 01, 2001 EXTREME FRACTIONATION OF PLATINUM GROUP ELEMENTS IN VOLCANOGENIC MASSIVE SULFIDE DEPOSITS Yuanming Pan; Yuanming Pan Department of Geological Sciences, University of Saskatchewan, Saskatoon, Canada SK S7N 5E2 *Corresponding author: e-mail, yuanming.pan@usask.ca Search for other works by this author on: GSW Google Scholar Qianli Xie Qianli Xie Department of Geological Sciences, University of Saskatchewan, Saskatoon, Canada SK S7N 5E2 Search for other works by this author on: GSW Google Scholar Author and Article Information Yuanming Pan Department of Geological Sciences, University of Saskatchewan, Saskatoon, Canada SK S7N 5E2 Qianli Xie Department of Geological Sciences, University of Saskatchewan, Saskatoon, Canada SK S7N 5E2 *Corresponding author: e-mail, yuanming.pan@usask.ca Publisher: Society of Economic Geologists Received: 17 Jul 2000 Accepted: 07 Nov 2000 First Online: 19 Apr 2017 Online ISSN: 1554-0774 Print ISSN: 0361-0128 Economic Geology Economic Geology (2001) 96 (3): 645–651. https://doi.org/10.2113/gsecongeo.96.3.645 Article history Received: 17 Jul 2000 Accepted: 07 Nov 2000 First Online: 19 Apr 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Yuanming Pan, Qianli Xie; EXTREME FRACTIONATION OF PLATINUM GROUP ELEMENTS IN VOLCANOGENIC MASSIVE SULFIDE DEPOSITS. Economic Geology 2001;; 96 (3): 645–651. doi: https://doi.org/10.2113/gsecongeo.96.3.645 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEconomic Geology Search Advanced Search Abstract Platinum group elements (PGE) and gold in selected ore samples and associated lithologies from four well-known volcanogenic massive sulfide (VMS) districts (i.e., the kuroko Zn-Pb-Cu deposits of Hokuroku, Japan; the Besshi Cu-Zn deposit of Shikoku, Japan; the Cu-Zn-Au-Ag deposits of Manitouwadge, Ontario, Canada; and the Cu-Zn-Co deposits of Outokumpu, Finland) have been determined by nickel sulfide fire assay preconcentration, tellurium coprecipitation, and inductively coupled plasma mass spectrometry analysis. The chalcopyrite-rich samples associated with mafic-ultramafic rocks from Besshi, Manitouwadge, and Outokumpu locally contain elevated contents of Pd (up to 1.8 ppm), Rh (up to 0.8 ppm), and Au (up to 14 ppm), whereas those of the kuroko deposits hosted by felsic volcanic rocks are poor in PGE. Moreover, the chalcopyrite-rich samples and cordierite-orthoamphibole gneisses show extreme fractionation of Au, Ir, Pd, and Pt (Au/Ir values up to 108,000; Pd/Ir, up to 29,500; and Pd/Pt, up to 2,100), which are somewhat similar to previously reported Au/Ir and Pd/Ir values in modern sea-floor hydrothermal sulfides but are significantly higher than those in magmatic Ni-Cu sulfides. The extreme fractionation of Au, Ir, Pd, and Pt in these volcanogenic massive sulfide deposits cannot be explained by the relative metal solubilities in sea-floor hydrothermal fluids but may be related to local remobilization of PGE and Au during late hydrothermal alteration and/or metamorphism. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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 score0.073
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)0.0250.001

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 head0.016
GPT teacher head0.197
Teacher spread0.182 · 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

Citations19
Published2001
Admission routes2
Has abstractyes

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