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Record W3217087533 · doi:10.1130/g49431.1

Microstructural evidence for convection in high-silica granite

2021· article· en· W3217087533 on OpenAlexafffund
Brendan Dyck, Marian B. Holness

Bibliographic record

VenueGeology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSight Research UK
KeywordsGeologySillCrystal (programming language)CrystallizationQuartzConvectionMineralogyGeochemistryChemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract High-silica (>70 wt% SiO2) granites (HSGs) are critical carriers of tin, copper, and other melt-incompatible elements, yet much remains unknown about the mechanisms responsible for their formation. One of the key issues is the apparent lack of evidence for crystal-melt segregation (e.g., modal layering), without which little can be inferred about the dynamics (or lack thereof) of crystallizing HSGs. We examined the crystallographic orientation relationships of clustered quartz crystals from the 300-m-thick Bobbejaankop sill, Bushveld Complex, South Africa. We report an inward increase in the number density and size of quartz clusters toward the central horizon of the sill, coinciding with a significant increase in concentrations of tin, copper, and tungsten. The majority of crystal pairs within each cluster exhibit coincident-site lattice orientation relationships, representing low grain-boundary energy configurations. These clusters must have formed by synneusis in a magmatic environment where crystals could have moved freely, rotating into low-energy orientations on contact. We argue that this not only demonstrates that 100-m-scale crystal-poor and liquid-rich regions can be present in bodies of HSG, but also that such bodies can undergo long-lived convection during crystallization, driven by downwards movement of crystal-rich plumes at the roof, without significant crystal-melt segregation. This dynamic behavior provides a mechanism to homogenize major-element distribution across HSGs and to concentrate highly incompatible and economic elements into central mineralized horizons.

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 score0.050
Threshold uncertainty score0.993

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)0.0080.000

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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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

Citations16
Published2021
Admission routes2
Has abstractyes

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