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Record W2044026272 · doi:10.1118/1.2968095

Measurement of multiple scattering of 13 and electrons by thin foils

2008· article· en· W2044026272 on OpenAlexaffabout
C. K. Ross, M McEwen, A McDonald, C. D. Cojocaru, Bruce Faddegon

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsCarleton UniversityNational Research Council Canada
FundersNational Cancer InstituteNational Institutes of Health
KeywordsScatteringElectronPhysicsElectron scatteringOpticsMaterials scienceNuclear physicsMedical physicsComputational physics

Abstract

fetched live from OpenAlex

To model the transport of electrons through material requires knowledge of how the electrons lose energy and scatter. Theoretical models are used to describe electron energy loss and scatter and these models are supported by a limited amount of measured data. The purpose of this work was to obtain additional data that can be used to test models of electron scattering. Measurements were carried out using 13 and 20 MeV pencil beams of electrons produced by the National Research Council of Canada research accelerator. The electron fluence was measured at several angular positions from 0 degree to 90 degrees for scattering foils of different thicknesses and with atomic numbers ranging from 4 to 79. The angle, theta 1/e at which the fluence has decreased to 1/e of its value on the central axis was used to characterize the distributions. Measured values of theta 1/e ranged from 1.5 degrees to 8 degrees with a typical uncertainty of about 1%. Distributions calculated using the EGSnrc Monte Carlo code were compared to the measured distributions. In general, the calculated distributions are narrower than the measured ones. Typically, the difference between the measured and calculated values of theta 1/e is about 1.5%, with the maximum difference being 4%. The measured and calculated distributions are related through a simple scaling of the angle, indicating that they have the same shape. No significant trends with atomic number were observed.

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: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.236

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 communication0.0000.000
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 head0.034
GPT teacher head0.291
Teacher spread0.257 · 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

Citations33
Published2008
Admission routes2
Has abstractyes

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