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Record W2960226979 · doi:10.13016/uzz4-uitj

Characterization of the regional, crustal, and global distribution and abundance of the heat producing elements and their geoneutrino flux

2019· dissertation· en· W2960226979 on OpenAlexaboutno aff
Scott A. Wipperfurth

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
Fundersnot available
KeywordsCharacterization (materials science)Abundance (ecology)Flux (metallurgy)Distribution (mathematics)Heat fluxEnvironmental scienceGeologyGeographyPhysicsMaterials scienceNanotechnologyEcologyMathematicsBiologyHeat transferMetallurgyThermodynamics

Abstract

fetched live from OpenAlex

The amount and distribution of radiogenic power generation from the heat producing elements (HPE) U, Th, and K in the Earth is not well constrained. Compositional estimates of these elements vary by a factor of three in the bulk-Earth and 30 in the mantle after removal of the continental crust contribution. Understanding the total power derived from these elements is critical to understanding the power driving the Earth as they supply fuel to the geodynamo and mantle convection. The decay of HPE's produce particles called geoneutrinos and the measurement of the geoneutrino flux reveals the frequency of decay and the abundances of these elements in the Earth. The total geoneutrino flux can be categorized into three major contributors: the dominant component from the nearest 500 km of continental crust surrounding the detector and slightly smaller sub-equal contributions from the remaining global continental crust and the mantle. The negligible amount of HPE's within the core was tested by a mass-balance of the Th/U derived from Pb isotopes (κ_Pb). Each Earth layer was attributed a κ_Pb from representative samples with associated weighting factor from the estimated mass of U in each reservoir. The radiogenic power in the core from U and Th was constrained to ~0.03 terra-watts (median), emphasizing the core's negligible geoneutrino luminosity. To unravel the contribution from the inaccessible mantle to the signal at a detector one must build a physical and chemical description of the local and global crust. The 50x50 km regional geoneutrino flux surrounding the SNO+ detector (Sudbury, Canada) was modeled. 112 geologic samples were analyzed for their U, Th, K abundances and combined with a 3D physical model of the region. To supplement this, the methodology of Huang et al. (2013) was applied to an updated geophysical model for the bulk-crust to predict the global crustal signal at SNO+ and other detectors. Variable correlation is addressed and uncertainties from density, seismic velocity, crustal thickness, and abundances propagated. This dissertation explores the amount and distribution of HPE's within the Earth and their geoneutrino flux through geochemical and geophysical modeling on regional, crustal, and global scales. Together, the results update our understanding of the Earth's geoneutrino flux and the uncertainties still in the 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 communication0.0000.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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