Charged Particle Transport in Magnetic Fields in the EGSnrc Monte Carlo Code System
Bibliographic record
Abstract
The advent of magnetic resonance guided radiation therapy provides a promising technology for dealing with tumour motion and anatomical variations during treatment.These machines possess a variety of beam energies, geometrical configurations, and different magnetic field strengths.Although photon beams do not directly experience the influence of the magnetic field, electrons set in motion will curve and impact dose distributions.Clinical reference dosimetry protocols rely on correction factors which account for the change in detector response for different beam qualities in the absence of a magnetic field.The effect of the magnetic field poses challenges for dosimetry, as ion chambers and solid state detectors respond disproportionately to the actual change in the dose to the media in the presence of the magnetic field.This necessitates an adaptation of current dosimetry protocols through calculation of high precision magnetic field and beam quality correction factors which account for detector response variation.In this work, charged particle transport in magnetic fields is implemented in EGSnrc and is shown to pass the Fano cavity test at the 0.1 % level.Further good agreement with experimental ion chamber measurements is shown, and important effects such as air gaps and the unknown sensitive volume of the chamber are determined to cause several percent variation in the calculated ion chamber dose.Ion chamber magnetic field correction factors are then evaluated for over thirty cylindrical ionization chamber and a select number of parallel-plate chambers.Magnetic field correction factors for the majority of cylindrical chambers are within 1 % of unity, while parallel-plate chambers require correction factors on the order of several percent and, unlike cylindrical chambers, no optimal orientation is available to reduce the effect of the magnetic field.The %dd(10) x beam-quality specifier is shown to have a strong dependence of the magnetic field strength, and the TPR 20 10 is determined to be the optimal beam-quality specifier in magnetic fields.Collectively, this work contributes to the EGSnrc gold standard Monte Carlo code and to the evolving field of clinical reference dosimetry in magnetic fields.support.Dave's door has always been open when I needed help, and his insights and calm manner have always helped point the way forward.I have been truly lucky in my choice of supervisor and it is one of the best decisions I have ever made.I would also like to thank all of my friends, office mates, and colleagues at
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".