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Record W2010144444 · doi:10.1107/s090904951100344x

Use of Soller slits to remove reference foil fluorescence from transmission spectra

2011· article· en· W2010144444 on OpenAlexaff
Justin J. Tse, Graham N. George, Ingrid J. Pickering

Bibliographic record

VenueJournal of Synchrotron Radiation · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFOIL methodMaterials scienceX-ray absorption spectroscopyCalibrationOpticsAbsorption (acoustics)IonTransmission (telecommunications)Fluorescence spectroscopyAbsorption spectroscopySpectroscopyFluorescenceAnalytical Chemistry (journal)PhysicsChemistryTelecommunications

Abstract

fetched live from OpenAlex

Measurement of X-ray absorption spectroscopy (XAS) in transmission is the method of choice for strong or concentrated samples. In a typical XAS experiment above 5 keV the sample is placed between the first (I(0)) and second (I(1)) ion chambers and a standard foil is placed between the second (I(1)) and third (I(2)) ion chambers for simultaneous calibration of energy during sample analysis. However, some fluorescence from the foil may be registered in I(1), causing anomalies in the transmission signal of the sample, especially when the sample edge jump is relatively small. To remedy this, Soller slits were constructed and placed between the foil and I(1) to minimize back-fluorescence from the foil. A comparison of blank and standard samples, measured with or without Soller slits or under a worst-case scenario, demonstrates the advantages of Soller slits when analyzing weak signal samples via transmission XAS.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.256
Teacher spread0.221 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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