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Record W2791816042 · doi:10.4095/306480

Laser ablation-inductively coupled plasma-mass spectrometric analysis of fluid inclusions from the Windy Craggy Cu-Co-Au volcanogenic massive sulphide deposit: method development and preliminary results

2018· report· en· W2791816042 on OpenAlexaff
Madison A. Schmidt, Jan M. Peter, Simon E. Jackson, Zhaoping Yang, M I Leybourne, D Layton-Mathews

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsLaser ablationFluid inclusionsInductively coupled plasma mass spectrometryAblationGeologyInductively coupled plasmaPlasmaAnalytical Chemistry (journal)MineralogyChemistryLaserMetallurgyMaterials scienceMass spectrometryEnvironmental chemistryChromatographyPhysicsQuartzOpticsEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

There is increasing recognition that there is a variable magmatic component to mineralizing fluids in volcanogenic massive sulphide (VMS) deposit formation. A previous fluid inclusion study conducted on the Windy Craggy Cu-Co-Au deposit in northwestern British Columbia documented primary inclusion fluids salinities that are higher than typical VMS fluids. The previous study concluded that the high salinity indicates a magmatic contribution to the ore-forming system. This makes Windy Craggy an ideal study location to test if there is in fact a magmatic influence on the fluids and to quantify that contribution. Preliminary results of this study show fluids consistent in salinity and temperature with those observed in the previous study. Fluids with salinities between 6.2 and 12.2 weight % NaCl equivalent are documented. Laser ablation ICP-MS analysis of these inclusions detects Na, K, Ca, Cu, Sr, Sn, Sb, Ba and Pb as well as trace elements of potential magmatic origin, including Au, W, Sn, In and Bi. Due to the multiple possible sources of Sn, we will be focusing on other potential magmatic elements such as Au, Bi and In as the study progresses. The small number of samples analyzed to date precludes us from making definitive conclusions. However, the detection of some potential magmatic elements in 17 inclusions is promising.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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