An experimental feasibility study on the use of scattering foil free beams for modulated electron radiotherapy
Bibliographic record
Abstract
The potential benefit of using scattering foil free beams for delivery of modulated electron radiotherapy is investigated in this work. Removal of the scattering foil from the beamline showed a measured bremsstrahlung tail dose reduction just beyond R(p) by a factor of 12.2, 6.9, 7.4, 7.4 and 8.3 for 6, 9, 12, 16 and 20 MeV beams respectively for 2 × 2 cm(2) fields defined on-axis when compared to the clinical beamline. Monte Carlo simulations were matched to measured data through careful tuning of source parameters and the modification of certain accelerator components beyond the manufacturer's specifications. An accelerator model based on the clinical beamline and one with the scattering foil removed were imported into a Monte Carlo-based treatment planning system (McGill Monte Carlo Treatment Planning). A treatment planning study was conducted on a test phantom consisting of a PTV and two distal organs at risk (OAR) by comparing a plan using the clinical beamline to a plan using a scattering foil free beamline. A DVH comparison revealed that for quasi-identical target coverage, the volume of each OAR receiving a given dose was reduced, thus reducing the dose deposited in healthy tissue.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".