Epp: A <scp>C</scp>++ EGSnrc user code for x‐ray imaging and scattering simulations
Bibliographic record
Abstract
PURPOSE: Easy particle propagation (Epp) is a user code for the EGSnrc code package based on the c+ + class library egspp. A main feature of egspp (and Epp) is the ability to use analytical objects to construct simulation geometries. The authors developed Epp to facilitate the simulation of x-ray imaging geometries, especially in the case of scatter studies. While direct use of egspp requires knowledge of c+ +, Epp requires no programming experience. METHODS: Epp's features include calculation of dose deposited in a voxelized phantom and photon propagation to a user-defined imaging plane. Projection images of primary, single Rayleigh scattered, single Compton scattered, and multiple scattered photons may be generated. Epp input files can be nested, allowing for the construction of complex simulation geometries from more basic components. To demonstrate the imaging features of Epp, the authors simulate 38 keV x rays from a point source propagating through a water cylinder 12 cm in diameter, using both analytical and voxelized representations of the cylinder. The simulation generates projection images of primary and scattered photons at a user-defined imaging plane. The authors also simulate dose scoring in the voxelized version of the phantom in both Epp and DOSXYZnrc and examine the accuracy of Epp using the Kawrakow-Fippel test. RESULTS: The results of the imaging simulations with Epp using voxelized and analytical descriptions of the water cylinder agree within 1%. The results of the Kawrakow-Fippel test suggest good agreement between Epp and DOSXYZnrc. CONCLUSIONS: Epp provides the user with useful features, including the ability to build complex geometries from simpler ones and the ability to generate images of scattered and primary photons. There is no inherent computational time saving arising from Epp, except for those arising from egspp's ability to use analytical representations of simulation geometries. Epp agrees with DOSXYZnrc in dose calculation, since they are both based on the well-validated standard EGSnrc radiation transport physics model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.129 | 0.091 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".