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Record W175459856 · doi:10.4225/03/58b4b9ea22970

Structure and dynamics of intrusion-hosted magmatic ni-cu sulphide deposits: insights from analogue experiments & Voisey’s Bay (Canada)

2017· dissertation· en· W175459856 on OpenAlexaboutno aff
Benoit-Michel Saumur

Bibliographic record

VenueFigshare · 2017
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyMaficGeochemistryIntrusionMagma chamberMagmaIgneous rockBrecciaMineralization (soil science)MagmatismBasaltTectonicsSeismologyVolcano

Abstract

fetched live from OpenAlex

Magmatic Ni‐Cu±PGE sulphide deposits such as Voisey’s Bay (Canada), Noril’sk (Russia) and Jinchuan (China), are hosted in mafic magma conduits and/or intrusions. However, the physics and dynamics of these systems are poorly understood because of the high density (4200 kg/m3) and low viscosity (~0.01 Pa s) of sulphide liquid, and its immiscibility with respect to silicate magma. The aim of this thesis is to elucidate the plutonic, structural and dynamic controls on the genesis of intrusion‐hosted Ni‐Cu magmatic sulphide deposits. This research comprises fieldwork at Voisey’s Bay, analogue experiments on the withdrawal of sulphide liquid from magma chambers, and the application of new and previous analytical solutions to maficsulphide magmatic systems. Fieldwork consisted of structural mapping of the Voisey’s Bay Intrusion (VBI) and surrounding wall rock gneisses using field data, borehole data, televiewer data and structural core logging. To first order, the VBI consists of an upper chamber and a lower chamber, which are connected by a complex network of dykes. The geometry of the VBI and its associated ore bodies is controlled by a complex interplay of internal igneous and pre‐ to syn‐emplacement external tectonic processes. Wall rocks of the VBI were affected by at least three pre‐emplacement ductile deformation events, and two pre‐ to syn‐emplacement brittle deformation events. The locations of magmatic sulphide mineralization are strongly controlled by the interaction of dykes with pre‐ and syn‐emplacement wall rock structures. Wall‐rocks exerted a primary control on intrusion geometry, which affected magma flow dynamics and locally promoted the deposition of magmatic sulphide. The internal structure of the upper chamber of the VBI shows evidence for assembly from the top‐down by three major events of chamber construction fed by multiple pulses of magma. Only the final inputs of magma, associated with the feeder dykes of the VBI, contributed massive sulphide mineralization. The emplacement of the VBI occurred by floor depression, and was partly controlled by localized reactivation of pre‐emplacement wall rock structure. Analogue experiments, supported by theoretical considerations, indicate that dense sulphide liquid accumulated at the bottom of magma staging chambers can be mobilized and withdrawn from these chambers if it is entrained within relatively buoyant mafic magma. Under transitional flow conditions (Reynolds number, Re = 10‐1000), draw‐up of sulphide is highly sensitive to flow rates and the viscosities of the mafic magma. Draw‐up heights on the order of 1‐10 meters are predicted in highly dynamic inertial systems (Re > 1000), which is sufficient to explain the entrainment of large volumes of sulphide liquid into the upper parts of mafic magmatic systems. Because of its high density, low viscosity, its high thermal conductivity and its low solidus temperatures with respect to mafic magmas, sulphide liquid is mobile and can percolate downwards late in the emplacement history of an intrusive system. Sulphide percolation into brittle wall rock is partly controlled by its “critical accumulation height”, above which ponded sulphide is able to percolate downwards into wall rock anisotropies. Active deformation is necessary to produce larger scale (dm to 10m) injections of pure sulphide liquid into wall rock.

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)0.001
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 score0.714
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.1990.000

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 head0.014
GPT teacher head0.214
Teacher spread0.200 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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