SU‐D‐BRC‐06: Experimental and Monte Carlo Studies of Fluence Corrections for Graphite Calorimetry in Proton Therapy
Bibliographic record
Abstract
Purpose: For photon and electron beams, the standard device used to measure absorbed dose is a calorimeter. Standards laboratories are currently working on the establishment of graphite calorimeters as a primary standard for proton beams. To provide a practical method for graphite calorimetry, it is necessary to convert dose to graphite to dose to water, requiring knowledge of the water‐to‐graphite stopping‐power ratio and the fluence correction factor. This study aims to present a novel method to determine fluence corrections experimentally, and to apply this methodology to low‐ and high‐energy proton beams. Methods: Measurements were performed in 60 MeV and 180 MeV proton beams. Experimental information was obtained from depth‐dose ionization chamber measurements performed in a water phantom. This was repeated with different thicknesses of graphite plates in front of the water phantom. One distinct advantage of this method is that only ionization chamber perturbation factors for water are required. Fluence corrections were also obtained through Monte Carlo simulations for comparison with the experiments. Results: The experimental observations made in this study confirm the Monte Carlo results. Overall, fluence corrections between water and graphite increased with depth, with a maximum correction of 1% for the low‐energy beam and 4% for the high‐energy beam. The results also showed that a fraction of the secondary particles generated in proton therapy beams do not have enough energy to cross the ionization chamber wall; thus, their contribution is not accounted for in the measured fluence corrections. This effect shows up as a discrepancy in fluence corrections of 1% and has been confirmed by simulations of the experimental setup. Conclusion: Fluence corrections derived by experiment do not account for low‐energy secondary particles that are stopped in the ion chamber wall. This work will contribute to a practical graphite calorimetry technique for determining absolute dose to water in proton beams.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".