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Record W3179067815 · doi:10.1038/s43247-021-00205-8

The largest plagiogranite on Earth formed by re-melting of juvenile proto-continental crust

2021· article· en· W3179067815 on OpenAlexaff
Hamed Gamal El Dien, Zheng‐Xiang Li, Mohamed Abu Anbar, Luc S. Doucet, J. Brendan Murphy, Noreen J. Evans, Xiaoping Xia, Jiangyu Li

Bibliographic record

VenueCommunications Earth & Environment · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsSt. Francis Xavier University
FundersAustralian Research CouncilAustralian Government
KeywordsGeologyZirconContinental crustCrustGeochemistryMantle (geology)Oceanic crustHydrothermal circulationPartial meltingTectonicsSubductionPaleontology

Abstract

fetched live from OpenAlex

Abstract The growth of continental crust through melt extraction from the mantle is a critical component of the chemical evolution of the Earth and the development of plate tectonics. However, the mechanisms involved remain debated. Here, we conduct petrological and geochemical analyses on a large (up to 5000 km2) granitoid body in the Arabian-Nubian shield near El-Shadli, Egypt. We identify these rocks as the largest known plagiogranitic complex on Earth, which shares characteristics such as low potassium, high sodium and flat rare earth element chondrite-normalized patterns with spatially associated gabbroic rocks. The hafnium isotopic compositions of zircon indicate a juvenile source for the magma. However, low zircon δ18O values suggest interaction with hydrothermal fluids. We propose that the El-Shadli plagiogranites were produced by extensive partial melting of juvenile, previously accreted oceanic crust and that this previously overlooked mechanism for the formation of plagiogranite is also responsible for the transformation of juvenile crust into a chemically stratified continental crust.

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 score0.007
Threshold uncertainty score0.014

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 science0.0000.001
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 head0.017
GPT teacher head0.204
Teacher spread0.188 · 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

Citations34
Published2021
Admission routes1
Has abstractyes

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