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A novel beam width doubling double crystal monochromator -some preliminary findings

2013· article· en· W1965577972 on OpenAlexafffundabout
S. Boire, Ying Zhu, George Belev, Nazanin Samadi, W Szyszkowski, D. Chapman

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersNational Research Council CanadaWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMonochromatorOpticsBent molecular geometryBeam (structure)BeamlineBeam diameterSkewCrystal (programming language)Full width at half maximumPhysicsMaterials scienceComputer scienceLaser beamsLaser

Abstract

fetched live from OpenAlex

The maximum useable beam width at the Biomedical Imaging and Therapy (BMIT) beamline at the Canadian Light Source (CLS) is suitable for most imaging applications. But access to a wider beam would benefit many programs especially computed tomography where the beam width defines the largest sample that can be imaged. A double crystal bent Laue monochromator capable of doubling the width of the incident beam is proposed; this is possible by taking advantage of symmetric off-axis, or skew reflections in the crystals. A preliminary experiment to establish proof of concept for this design has been completed using a double crystal unbent Laue system. Results are presented showing the beam width doubling from 28.3mm to 56.6mm and the effect of the skew reflections on the monochromaticity of the exit beam. Further work on this monochromator will include an investigation into the choice of reflections, a study of the effect on the change in energy across the exit beam, the development of strategies to minimize the effect of the beam overlap region downstream from the monochromator and the development of an alignment process for the double crystal bent Laue 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 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)
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 score0.340
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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 teacher head, not a consensus.

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

Citations0
Published2013
Admission routes3
Has abstractyes

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