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Record W2171195698 · doi:10.1088/0031-9155/50/16/008

Analysis of urinary stone components by x-ray coherent scatter: characterizing composition beyond laboratory x-ray diffractometry

2005· article· en· W2171195698 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

VenuePhysics in Medicine and Biology · 2005
Typearticle
Languageen
FieldMaterials Science
TopicRadiation Shielding Materials Analysis
Canadian institutionsRobarts Clinical TrialsCancer Care OntarioWestern University
FundersCanadian Institutes of Health Research
KeywordsX-rayMaterials scienceImaging phantomSuperposition principleDiffractionX-ray crystallographyOpticsPhysics

Abstract

fetched live from OpenAlex

Monoenergetic x-ray diffraction (XRD) analysis is an established standard for the assessment of urinary stone composition. The inherent low energy of x-rays used (8 keV), however, restricts penetration depth and imposes a requirement for small powdered samples. A technique capable of producing detailed information regarding component structural arrangements in calculi non-destructively would provide clearer insights into causes of formation and subsequent growth and allow the selection of more appropriate courses of therapy. We describe a new method based on the detection of coherent scatter (CS) in stone components using polyenergetic x-rays (70 kVp) from diagnostic equipment. While the higher energy allows the analysis of intact calculi, the polyenergetic source causes an angular broadening of measured CS patterns. We show that it is possible to relate the polyenergetic (CS) and monoenergetic (XRD) measurements through a superposition integral of the monoenergetic XRD cross-section with a function representative of the polyenergetic spectrum used in CS. Experimentally acquired diffractometry cross-sections of the seven major urinary stone components were subjected to this operation, revealing good agreement of diffraction features with CS. Therefore, our CS analysis is sensitive to stone component structure, similar to conventional XRD analysis. This indicates that CS analysis can be used as a basis to classify urinary calculi by composition. The potential of identifying stone components non-destructively was demonstrated from a tomographic CS analysis of a stone-mimicking phantom. Tomographic composition maps were generated from CS patterns, showing the structural arrangement of multiple stone components within the phantom. CS analysis has the ability to detect components in the presence of many others. The ability to perform CS measurements in intact calculi would allow for the identification of stone structures critical to patient metaprophylaxis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.069
GPT teacher head0.345
Teacher spread0.276 · 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