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Record W1554702183 · doi:10.1111/ter.12156

Isotopically diverse rhyolites coeval with the Columbia River Flood Basalts: evidence for mantle plume interaction with the continental crust

2015· article· en· W1554702183 on OpenAlexafffund
D. Colon, Ilya N. Bindeman, Richard A. Stern, Christopher M. Fisher

Bibliographic record

VenueTerra Nova · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaNational Science Foundation
KeywordsGeologyFlood basaltGeochemistryCrustTerraneBasaltCratonMantle plumeContinental crustZirconPhenocrystMantle (geology)Partial meltingYilgarn CratonEarth scienceVolcanic rockVolcanoLithospherePaleontologyTectonicsVolcanism

Abstract

fetched live from OpenAlex

Abstract The Columbia River Flood Basalts (CRB) of the northwestern USA are coeval with eruptions of several thousand km3 of rhyolite. A broad survey of major phenocryst oxygen isotopes and of O and Hf isotopes in zircons from these rhyolites reveals significant diversity in inferred δ18Omelt values, ranging from +1.9 to +10.5‰ (SMOW), and in zircon Hf isotope compositions, which range from εHf = −39 to +9. This newly identified isotopic diversity shows that the syn‐CRB rhyolites were derived from high‐percentage melting of the crust. Low‐δ18O rhyolites, which fingerprint the melting of hydrothermally altered crust, are concentrated at the edge of the North American craton. This suggests that the conditions of crustal heating, faulting, and hydrothermal alteration required for the production of these rhyolites were concentrated there by the contrasts in crustal thickness and rheology associated with the boundary between the North American craton and younger accreted terranes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.257
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2015
Admission routes2
Has abstractyes

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