MétaCan
Menu
Back to cohort
Record W2982233202 · doi:10.4095/296689

Geochemical composition of chromite from Alexo komatiite in the western Abitibi greenstone belt: Implications for mineral exploration

2015· report· en· W2982233202 on OpenAlexaff
Philippe Pagé, Julien Méric, M G Houlé

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsChromiteGreenstone beltGeochemistryGeologyMineralArcheanMetallurgyMaterials science

Abstract

fetched live from OpenAlex

This study, which focuses on the composition of chromite from mineralized and unmineralized komatiitic flows and sills from the Alexo Mine area in Dundonald Township, within the western Abitibi greenstone belt, aims to develop new exploration tools for poorly exposed mineralized komatiitic systems. It is possible to clearly identify chromite derived from massive sulphide (having very high Cr# and depleted Ru content) from chromite derived from barren and poorly mineralized samples based on its composition. LA-ICPMS analyses show that chromite from massive sulphide are depleted in Al, Ni, and Mg, and are enriched in Ti, Zn, Mn, Fe and V compared to chromite from barren samples; however, alteration can also modify chromite chemistry. Samples from the Hart deposit are pervasively altered and their chromite compositions are enriched in Fe, Zn, Co, and Mn, and are depleted in Mg. We propose a binary diagram of Ni/Mn versus Ni/Cr ratios which can be used to clearly discriminate between sulphide segregation prior to chromite crystallization and later superimposed alteration. Mass balance calculations show that chromite does fractionate and concentrate Ir-group platinum-group elements (IPGE: Os, Ir, Ru) and Rh but that chromite contribution to the whole-rock IPGE and Rh budget is rather limited, and for mineralized samples, this contribution is even smaller. From these results, it is clear that IPGE+Rh-rich phases (nano- to micro- platinum-group minerals) are needed to account for the IPGE and Rh contents in whole-rock geochemistry.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.098
GPT teacher head0.328
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicMetal Extraction and BioleachingFrench-language works237,207