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Record W2904233307 · doi:10.3749/canmin.1800021

Ghosts of Apatite Past: Using Hyperspectral Cathodoluminescence and Micro-Geochemical Data To Reveal Multi-Generational Apatite in the Gifford Creek Carbonatite Complex, Australia

2018· article· en· W2904233307 on OpenAlexvenueno aff
Paul Slezak, Carl Spandler, Kevin Blake

Bibliographic record

VenueThe Canadian Mineralogist · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
FundersAnalytical Center for the Government of the Russian Federation
KeywordsCarbonatiteCitationIconApatiteGeologyArchaeologyLibrary scienceHistoryGeochemistryComputer science

Abstract

fetched live from OpenAlex

Apatite can host significant levels of trace elements, including REE, within its crystal lattice, making it particularly useful for deciphering geological events and processes. This study employs hyperspectral cathodoluminescence (CL) and in situ microchemical techniques to identify and characterize various generations of apatite occurring in the phoscorites, carbonatites, and fenites of the Gifford Creek Carbonatite Complex (GCCC), Western Australia. Hyperspectral CL revealed that apatite crystals in all samples have complex internal zoning, including multiple distinct generations, with zones of relatively bright CL generally having more complex spectra compared to darker CL zones. Most of the CL spectra have prominent sharp peaks at similar to 1.4 eV and similar to 2.l eV as well as a broad peak between 2.3 eV and 3.5 eV. We relate these different peaks to individual REE activators and groups of activators, in particular Nd3+, Eu3+, Sm3+, and Ce3+. Trace element analyses of apatite confirm the relative enrichment of REE in the CL brighter zones. Most apatite generations exhibit concave-down to sinusoidal REY patterns lacking Eu anomalies, but often feature distinct negative Y anomalies. The depletion in LREE is interpreted to be due to LREE sequestration into monazite, which is relatively abundant in most of the samples. Most apatite samples contain very low Si contents, but appreciable Na, so REE incorporation into apatite was primarily via a coupled substitution of REE + Na replacing 2Ca, which is consistent with the highly alkaline, low SiO(2 )environment under which the apatite formed. Based on the combined trace-element signatures and CL textures, we interpret the multiple generations of apatite to reflect magmatic growth from alkaline magmas followed by recrystallization during subsequent metamorphic/hydrothermal events. The notable exception is the apatite core domains from a fenite sample that contain relatively high Si and Mn contents, low Sr, and relatively HREE-enriched REY patterns with distinct negative Eu anomalies. This apatite is interpreted to be relict from the granitic precursor to fenitization. The apatite samples also show systematic compositional variations across the GCCC, with apatite from phoscorite samples from the southeast part of the complex containing higher Sr, lower Gd/Ce, and lower lambda(3 )values (normalized REE pattern inflections) compared to apatite from the northwest part of the complex. Recognition of these spatial variations in apatite compositions from the intra-grain micro-scale through to the district scale demonstrates the utility of combining advanced petrographic methods, such as hyperspectral CL, with micro-chemical analysis to reveal complex geological records preserved in apatite. As apatite is a common accessory mineral, these techniques may be more broadly applicable to igneous source tracing, understanding metamorphic and/or metasomatic processes, provenance studies from detrital mineral records, and studies of the evolution of ore systems.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

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

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 head0.211
GPT teacher head0.311
Teacher spread0.100 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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