Comparison of linear energy transfer scoring techniques in Monte Carlo simulations of proton beams
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Bibliographic record
Abstract
Monte Carlo (MC) simulations are commonly used to study linear energy transfer (LET) distributions in therapeutic proton beams. Various techniques have been used to score LET in MC simulations. The goal of this work was to compare LET distributions obtained using different LET scoring techniques and examine the sensitivity of these distributions to changes in commonly adjusted simulation parameters. We used three different techniques to score average proton LET in TOPAS, which is a MC platform based on the Geant4 simulation toolkit. We determined the sensitivity of each scoring technique to variations in the range production thresholds for secondary electrons and protons. We also compared the depth-LET distributions that we acquired using each technique in a simple monoenergetic proton beam and in a more clinically relevant modulated proton therapy beam. Distributions of both fluence-averaged LET (LETΦ) and dose-averaged LET (LETD) were studied. We found that LETD values varied more between different scoring techniques than the LETΦ values did, and different LET scoring techniques showed different sensitivities to changes in simulation parameters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it