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Record W3146949807 · doi:10.1107/s1600577521002496

The lower energy diffraction and scattering side-bounce beamline for materials science at the Canadian Light Source

2021· article· en· W3146949807 on OpenAlexafffundabout
Adam F. G. Leontowich, Ariel Gómez, Beatriz D. Moreno, David Muir, Denis M. Spasyuk, Graham King, Joel W. Reid, Chang‐Yong Kim, S. Kycia

Bibliographic record

VenueJournal of Synchrotron Radiation · 2021
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsUniversity of GuelphCanadian Light Source (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of SaskatchewanCanadian Light Source
KeywordsBeamlineWigglerMonochromatorOpticsDiffractionAdvanced Photon SourceSynchrotronSynchrotron radiationScatteringBragg's lawPhotonPhysicsMaterials scienceHigh-energy X-raysPhoton energyBeam (structure)Nuclear physics

Abstract

fetched live from OpenAlex

A new diffraction beamline for materials science has been built at the Canadian Light Source synchrotron. The X-ray source is an in-vacuum wiggler with a 2.5 T peak magnetic field at 5.2 mm gap. The optical configuration includes a toroidal mirror, a single side-bounce Bragg monochromator, and a cylindrical mirror, producing a sub-150 µm vertical × 500 µm horizontal focused beam with a photon energy range of 7–22 keV and a flux of 1012 photons per second at the sample position. Three endstations are currently open to general users, and the techniques available include high-resolution powder diffraction, small molecule crystallography, X-ray reflectivity, in situ rapid thermal annealing, and SAXS/WAXS. The beamline design parameters, calculated and measured performance, and initial experimental results are presented to demonstrate the capabilities for materials science.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0700.020

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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

Citations78
Published2021
Admission routes3
Has abstractyes

Explore more

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