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Record W3197218989 · doi:10.1029/2021gc009691

Heat Generation in Cratonic Mantle Roots—New Trace Element Constraints From Mantle Xenoliths and Implications for Cratonic Geotherms

2021· article· en· W3197218989 on OpenAlexafffund
T. McIntyre, Kristina Kublik, Claire A. Currie, D. Graham Pearson

Bibliographic record

VenueGeochemistry Geophysics Geosystems · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsGeologyXenolithGeochemistryKimberliteMantle (geology)PeridotiteOlivineCratonMetasomatismPetrologyLithosphereHotspot (geology)GeophysicsTectonicsPaleontology

Abstract

fetched live from OpenAlex

Abstract Heat generation within the cratonic lithospheric mantle (CLM) is an important but poorly determined parameter for constructing cratonic geotherms. Direct measurement of heat producing element (HPE: K, U, and Th) concentrations in bulk‐rock samples of cratonic mantle roots—provided as xenoliths in volcanic rocks such as kimberlites—is mostly compromised by infiltration of host melt into the xenoliths, resulting in over‐estimates of heat production. Here we use in situ methods (laser ablation inductively coupled plasma mass spectrometry) on minerals from a variety of cratonic mantle peridotites to avoid host‐magma contamination enabling new, more accurate determinations of heat production for a wide spectrum of model mantle lithologies. The most melt‐depleted, least metasomatized peridotites indicate that heat generation in un‐metasomatized depleted cratonic lithospheric mantle is negligible, at ∼0.00004 µW/m 3 , 10 2 to 10 3 times less than models that use more enriched or metasomatized compositions. Refertilized cratonic peridotites, typical of many kimberlite hosted xenoliths, have more elevated, but still low heat generation, of 0.006 µW/m 3 . We propose that the heat generation of typical cratonic mantle peridotite lies between these two bounds, that is, between 0.00004 and 0.006 µW/m 3 . Both values produce lower estimates of lithospheric thickness, by ∼10 to up to 80 km, depending on model assumptions, than estimates using higher HPE concentrations measured on bulk‐rock xenolith material.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.997

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)0.0030.000

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 head0.016
GPT teacher head0.218
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; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
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

Citations22
Published2021
Admission routes2
Has abstractyes

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