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Record W4225299090 · doi:10.1029/2022gl098541

Identification of High δ<sup>18</sup>O Adakite‐Like Granites in SE Tibet: Implication for Diapiric Relamination of Subducted Sediments

2022· article· en· W4225299090 on OpenAlexaff
Jian Xu, Xiaoping Xia, Christopher J. Spencer, Qiang Wang, Changqing Yin

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsAdakiteGeologySubductionGeochemistryCrustContinental crustOceanic crustSedimentary rockFelsicEarth sciencePaleontologyMaficTectonics

Abstract

fetched live from OpenAlex

Abstract Sediment relamination in subduction zones is posited to be important for the compositional evolution, physical structure and material recycling of the Earth. Despite support from numerical experimental modeling and geophysical observation, magmatic evidence for relamination is rare and difficult to identify in ancient and modern convergent systems. Here we report newly identified ca.32–27 Ma adakite‐like granites with high δ18O values (up to 10.38‰) from the Ailaoshan‐Red River (ASRR) shear zone in western Yunnan (SE Tibet). Their geochronological and compositional data strongly exhibits significant contributions from Permian‐Eocene sedimentary rocks in the lower crust (30–45 km). Our study provides further evidence that the lower crust may be partially composed of more felsic lithologies likely originating from rapid supracrustal material recycling via diapiric relamination of (meta)sedimentary material during Cenozoic‐age continental subduction. The ASRR adakite‐like granites thus represent clear magmatic evidence for sediment relamination in a subduction system.

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 score0.005
Threshold uncertainty score0.011

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 studies0.0000.001
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 head0.032
GPT teacher head0.285
Teacher spread0.254 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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