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Record W2004095600 · doi:10.1038/srep00182

Determination of total x-ray absorption coefficient using non-resonant x-ray emission

2011· article· en· W2004095600 on OpenAlexafffund

Bibliographic record

VenueScientific Reports · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsCanadian Light Source (Canada)University of SaskatchewanUniversity of Waterloo
FundersDivision of Materials ResearchCanadian Institutes of Health ResearchMaterials Research Science and Engineering Center, Harvard UniversityNatural Sciences and Engineering Research Council of CanadaCornell Center for Materials ResearchUniversity of SaskatchewanCanadian Light SourceNational Science Foundation
KeywordsMeasure (data warehouse)Analytical Chemistry (journal)Absorption spectroscopySpectroscopyFluorescenceAbsorption (acoustics)Yield (engineering)Saturation (graph theory)

Abstract

fetched live from OpenAlex

An alternative measure of x-ray absorption spectroscopy (XAS) called inverse partial fluorescence yield (IPFY) has recently been developed that is both bulk sensitive and free of saturation effects. Here we show that the angle dependence of IPFY can provide a measure directly proportional to the total x-ray absorption coefficient, µ(E). In contrast, fluorescence yield (FY) and electron yield (EY) spectra are offset and/or distorted from µ(E) by an unknown and difficult to measure amount. Moreover, our measurement can determine µ(E) in absolute units with no free parameters by scaling to µ(E) at the non-resonant emission energy. We demonstrate this technique with measurements on NiO and NdGaO(3). Determining µ(E) across edge-steps enables the use of XAS as a non-destructive measure of material composition. In NdGaO(3), we also demonstrate the utility of IPFY for insulating samples, where neither EY or FY provide reliable spectra due to sample charging and self-absorption effects, respectively.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.262
Teacher spread0.245 · 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 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

Citations65
Published2011
Admission routes2
Has abstractyes

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