MétaCan
Menu
Back to cohort
Record W2500815776 · doi:10.1063/1.4952876

An energy dispersive bent Laue monochromator for K-edge subtraction imaging

2016· article· en· W2500815776 on OpenAlexaff
Nazanin Samadi, Mercedes Martinson, Bassey Bassey, Ariel Gómez, George Belev, Dean Chapman

Bibliographic record

VenueAIP conference proceedings · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
Fundersnot available
KeywordsMonochromatorBent molecular geometryOpticsSubtractionEnhanced Data Rates for GSM EvolutionPhysicsEnergy (signal processing)GeometryMaterials scienceComputer scienceMathematicsArtificial intelligenceQuantum mechanicsArithmetic

Abstract

fetched live from OpenAlex

K-Edge Subtraction (KES) is a powerful synchrotron imaging method that allows the quantifiable determination of a contrast element (e.g. iodine) and matrix material (usually represented as water) in both projection imaging and computed tomography. A bent Laue monochromator has been developed that has very good focal and energy dispersive properties for KES. Approximately 5% of the vertical beam profile is involved in “edge crossing” energies, thus no splitter is employed as has been done with previous implementations where approximately 33% of the beam size was blocked. The beam can be narrowed vertically allowing a smaller crossover angle than a splitter based system which minimizes artifacts. The combination of good spatial resolution, energy dispersive properties, flux and a unique approach to data analysis make this system nearly ideal for KES.

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 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: none
Teacher disagreement score0.869
Threshold uncertainty score0.703

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 communication0.0000.001
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 head0.012
GPT teacher head0.273
Teacher spread0.261 · 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.

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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicAdvanced X-ray Imaging TechniquesFrench-language works237,207