Comparison between EGSnrc, Geant4, MCNP5 and Penelope for mono-energetic electron beams
Bibliographic record
Abstract
A simple geometry is chosen to highlight similarities and differences of current electron transport algorithms implemented in four Monte Carlo codes commonly used in radiation physics. Energy deposited in a water-filled sphere by mono-energetic electron beams was calculated using EGSnrc, Geant4, MCNP5 and Penelope as the radius of the sphere varied from 0.25 cm to 4.5 cm for beam energies of 0.5 MeV, 1.0 MeV and 5.0 MeV. The calculations were performed in single-scattering mode (where applicable) and in condensed history mode. A good agreement is found for the single-scattering calculations except for the in-air case at 0.5 MeV where differences increase with decreasing radius up to 5% between EGSnrc and Penelope. Differences between results calculated with the default user settings when compared to their own single-scattering modes are under 5% for all codes when the sphere is surrounded by vacuum, however, large differences occur for Geant4, MCNP5 and Penelope when air is introduced around the sphere. Finally, the parameters associated with the multiple scattering algorithms were tuned reducing these differences below 10% for these codes at the expense of increased computation time.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".