Design and validation of novel scattering foils for modulated electron radiation therapy
Bibliographic record
Abstract
Modulated Electron Radiation Therapy (MERT) continues to be an area of interest to various groups, however, the scattering foils used in beam flattening have not been optimized for this modality. In this work, the feasibility of novel scattering foils specifically designed for MERT is investigated using Monte Carlo methods. Different designs based on foil material, shape and thickness were analyzed. It was shown that low atomic number materials such as aluminum were optimal, while shaped foils such as those employed in current dual foil designs were not necessary. Aluminum foil thickness between 0.36 mm and 1.50 mm were capable of sufficiently broadening beams with energies between 12 MeV and 20 MeV respectively, with beams of lower energies receiving sufficient scatter from the treatment head components and air scatter. Finally, custom foils were manufactured based upon previously simulated designs and were placed into the beamline of a 2100 EX accelerator, and showed excellent agreement between the simulated and measured PDDs and profiles. Custom foils achieved higher dose rates on the central axis compared to the clinical foils by factors of 5.4, 4.9 and 4.5 for 12 MeV, 16 MeV and 20 MeV, respectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".