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Record W4389508554 · doi:10.1038/s41467-023-43845-4

Widespread PREMA in the upper mantle indicated by low-degree basaltic melts

2023· article· en· W4389508554 on OpenAlexaff
Ronghua Cai, Jingao Liu, D. Graham Pearson, Andrea Giuliani, Peter E. van Keken, Senan Oesch

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
FundersNational Key Research and Development Program of ChinaChina University of Geosciences, BeijingNational Natural Science Foundation of China
KeywordsMantle (geology)GeologyMantle convectionBasaltHotspot (geology)GeochemistryGeophysicsSubductionPaleontologyTectonics

Abstract

fetched live from OpenAlex

Studies of ocean island basalts have identified a Prevalent Mantle (PREMA) component as a fundamental feature of mantle geochemical arrays; however, its origin and distribution are highly controversial, including its potential link to plumes sourced in low-shear-wave velocity provinces (LLSVPs) above the core-mantle boundary. In this study, we interrogate the compositional systematics of ~ 3500 Cenozoic oceanic and continental sodic basalts to provide insights into the origin and distribution of PREMA. We find that low-degree basaltic melts with high Nb concentrations located away from deep-mantle plumes have PREMA-like Sr-Nd-Hf isotopic signatures, implying that PREMA is highly fusible and not exclusively associated with LLSVPs. Geochemical modelling and mantle convection simulations indicate that PREMA could have been generated soon after Earth accretion, experiencing only minimal melting or enrichment, and then scattered throughout the upper mantle, rather than being the result of mixing between depleted and enriched mantle components.

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 score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
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 head0.026
GPT teacher head0.255
Teacher spread0.230 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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