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Record W4317564832 · doi:10.1130/g50675.1

Diamonds reveal subducted slab harzburgite in the lower mantle

2023· article· en· W4317564832 on OpenAlexafffund
Nicole A. Meyer, Thomas Stachel, D. Graham Pearson, Richard A. Stern, Jeffrey W. Harris, Michael J. Walter

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Research Foundation
KeywordsGeologyMantle (geology)SubductionDiamondTransition zoneGeochemistryLithosphereMelt inclusionsMagnesiteSlabGeophysicsPaleontologyMaterials scienceTectonics

Abstract

fetched live from OpenAlex

Abstract Characterizing compositional heterogeneity in Earth’s lower mantle is critical to understanding its dynamics. Three low-nitrogen diamonds from Koffiefontein (South Africa), containing inclusion assemblages of ferropericlase ± orthopyroxene ± magnesite, constrain diamond formation in an Mg-rich lower-mantle environment. Ferropericlase inclusions have Mg# 82.7–88.5 and orthopyroxene inclusions (retrogressed bridgmanite) have Mg# 95.0–95.1 and mantle-like δ18O of +5.6‰ ± 0.2‰. Magnesite included in one diamond implicates carbonated fluids in diamond formation. High Mg# and low Ca, Al, and Na of the assemblage indicate a melt-depleted meta-harzburgitic environment, in contrast to more fertile compositions expected for primitive lower mantle. Extremely low Ca in orthopyroxene inclusions may reflect a combination of melt depletion and low equilibration temperatures at the time of trapping. Inclusion compositions implicate subducted oceanic slab meta-harzburgite as the host for diamond growth. Mantle-like δ18O of the orthopyroxene inclusions indicates unaltered oceanic lithosphere. Similar melt-depleted characteristics in lower-mantle inclusion assemblages worldwide support that meta-harzburgite is the dominant host of lower-mantle diamonds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations10
Published2023
Admission routes2
Has abstractyes

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