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Record W2579440784 · doi:10.1002/xrs.2743

Combined X‐ray diffraction and alpha particle X‐ray spectrometer analysis of geologic materials

2017· article· en· W2579440784 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueX-Ray Spectrometry · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyU.S. Geological Survey
KeywordsHomogeneity (statistics)DiffractionSpectrometerAtomic numberMineralMineralogyComputational physicsAnalytical Chemistry (journal)ChemistryMaterials sciencePhysicsOpticsAtomic physicsMathematicsStatisticsMetallurgy

Abstract

fetched live from OpenAlex

The shallow interrogation depth of the lightest elements (Na, Mg, Al, and Si) detected by the particle‐induced X‐ray emission branch of the Curiosity Rover's alpha particle X‐ray spectrometer suggests that the X‐rays of these elements very likely emerge from a single mineral grain. This reality violates the assumption of atomic homogeneity at the micron scale made in both existing spectrum‐reduction approaches for the alpha particle X‐ray spectrometer. Consequently, analytical results for these elements in igneous geochemical reference materials exhibit deviations from certified concentrations in a manner that can be related to the total alkali‐silica diagram. A computer code is introduced here to provide quantitative prediction of these deviations using the mineral abundances determined from X‐ray diffraction. The latter are converted to area coverage fractions to represent the sample surface, and a fundamental parameters computation predicts the elemental X‐ray yields from each mineral and sums these. In this process, the chemistry of each individual mineral has to be varied by an iterative simplex approach; X‐ray yields are computed and compared with the peak areas from the fit of the bulk sample. When the difference between mineral yields and peak areas for each element are minimized, the mineral formulae are set and elemental X‐ray yields provided. The ratio between the summed mineral X‐ray yields and the corresponding yields based on the homogeneity assumption may then be compared directly with the concentration deviations measured in our earlier work. For several rock types, good agreement is found, thereby consolidating our understanding of the effects of sample mineralogy on alpha particle X‐ray spectrometer results. Copyright © 2017 John Wiley & Sons, Ltd.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.268
Teacher spread0.257 · 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