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Record W2528315374 · doi:10.1144/sp446.5

Differences and similarities between emplacement models of kimberlite and basaltic maar-diatreme volcanoes

2016· article· en· W2528315374 on OpenAlexaff
Stephan Kurszlaukis, Volker Lorenz

Bibliographic record

VenueGeological Society London Special Publications · 2016
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsDe Beers (Canada)
Fundersnot available
KeywordsDiatremeMaarKimberliteGeologyVolcanoBasaltPhreatomagmatic eruptionXenolithGeochemistryPetrologyMagmaMantle (geology)

Abstract

fetched live from OpenAlex

Abstract Most kimberlite maar-diatreme volcanoes erupted during the Tertiary or earlier and therefore their tephra rings and, less often, their near-surface diatreme-filling deposits have usually been eliminated by erosion. Poorly eroded Quaternary non-kimberlite maar-diatreme volcanoes, especially those of mafic and ultramafic magma types, have the same diatreme size range (diameter and depth) as kimberlite pipes and show similar internal volcaniclastic diatreme lithofacies. In addition, these young volcanoes often have a more or less preserved tephra ring consisting of hundreds to perhaps a few thousand thin tephra beds. Volcanological analyses of the xenolith-rich primary volcaniclastic deposits both within these diatremes and in the tephra ring beds reflect phases of explosive pipe growth and are of convincingly phreatomagmatic origin. The similarities between non-kimberlite pipes and kimberlite pipes suggest to some researchers that phreatomagmatic processes were also responsible for pipe excavation processes in kimberlite maar-diatreme volcanoes. In contrast, other researchers have suggested that kimberlite maar-diatreme volcanoes were emplaced largely by magmatic processes as a consequence of exsolution and the explosive expansion of juvenile volatiles. We therefore analysed and compared some key geological features of kimberlite and ultrabasic to basic ‘basaltic’ maar-diatreme volcanoes to determine similarities and differences with respect to their emplacement behaviour.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.434

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.037
GPT teacher head0.232
Teacher spread0.195 · 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 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

Citations27
Published2016
Admission routes1
Has abstractyes

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