TH‐D‐BRB‐08: The Effect of Transverse Magnetic Fields on a Simulated In‐Line 6 MV Linac
Bibliographic record
Abstract
Purpose: The linac waveguide is subjected to large magnetic fringe fields in a linac‐MR hybrid system. An investigation is performed to determine the effect of transverse magnetic fields on a simulated in‐line 6 MV medical linac. Method and Materials: The program PARMELA was used calculate the electron beam loss per cavity with the linac waveguide subjected to external transverse fields. BEAMnrc and DOSXYZnrc were used to calculate the effect on 40×40 and 20×20 cm2 field dose profiles and depth dose curves with the linac submersed in a transverse magnetic field. DOSRZnrc was used to determine the heating per cavity as a result of the beam loss and COMSOL was used to determine the resulting cavity resonant frequency changes due to cavity heating. Lastly a calculation of leakage radiation caused by the excessive beam loss was performed using BEAMnrc. Results: The beam loss was calculated to be 5±1 22±1 and 49±1% over nominal for 2 4 and 6 G magnetic fields respectively. The transverse magnetic fields caused a shifting of the electron spatial distribution at the target which resulted in a lateral shift of the dose profiles making 14.4% of all points fail a 1%/1mm acceptance criterion at a 6 G field. Through asymmetric jaw positions the lateral shift in the dose profiles was reduced such that only 0.5% of all points failed. The frequency of the accelerating mode changed by 0.03 Hz due to heating and a total leakage radiation of 0.007% of the radiation field was calculated. Conclusion: The 6 MV linac investigated showed sufficient tolerance to be used in transverse magnetic fields larger than earth's field. The shifts observed in the dose profiles were reduced through asymmetric jaw positions such that only 0.5 % of the points failed a 1 %/ 1 mm criterion at 6 G.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".