Absolute prompt-gamma yield measurements for ion beam therapy monitoring
Bibliographic record
Abstract
Prompt-gamma emission detection is a promising technique for hadrontherapy monitoring purposes. In this regard, obtaining prompt-gamma yields that can be used to develop monitoring systems based on this principle is of utmost importance since any camera design must cope with the available signal. Herein, a comprehensive study of the data from ten single-slit experiments is presented, five consisting in the irradiation of either PMMA or water targets with lower and higher energy carbon ions, and another five experiments using PMMA targets and proton beams. Analysis techniques such as background subtraction methods, geometrical normalization, and systematic uncertainty estimation were applied to the data in order to obtain absolute prompt-gamma yields in units of prompt-gamma counts per incident ion, unit of field of view, and unit of solid angle. At the entrance of a PMMA target, where the contribution of secondary nuclear reactions is negligible, prompt-gamma counts per incident ion, per millimetre and per steradian equal to (124 ± 0.7stat ± 30sys) × 10(-6) for 95 MeV u(-1) carbon ions, (79 ± 2stat ± 23sys) × 10(-6) for 310 MeV u(-1) carbon ions, and (16 ± 0.07stat ± 1sys) × 10(-6) for 160 MeV protons were found for prompt gammas with energies higher than 1 MeV. This shows a factor 5 between the yields of two different ions species with the same range in water (160 MeV protons and 310 MeV u(-1) carbon ions). The target composition was also found to influence the prompt-gamma yield since, for 300/310 MeV u(-1) carbon ions, a 42% greater yield ((112 ± 1stat ± 22sys) × 10(-6) counts ion(-1) mm(-1) sr(-1)) was obtained with a water target compared to a PMMA one.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".