GEANT4 simulation of a range verification method using delayed <i>γ</i> spectroscopy of a <sup>92</sup> Mo marker
Bibliographic record
Abstract
In this work, we propose a novel technique for in-vivo proton therapy range verification. This technique makes use of a molybdenum hadron tumour marker, implanted at a short distance from the clinical treatment volume. Signals emitted from the marker during treatment can provide a direct measurement of the proton beam energy at the marker's position. Fusion-evaporation reactions between the proton beam and marker nucleus result in the emission of delayed characteristic γ rays, which are detected off-beam for an improved signal-to-noise ratio. In order to determine the viability of this technique and to establish an experimental setup for future work, the Monte Carlo package GEANT4 was used in combination with ROOT to simulate a treatment scenario with the new method outlined in this work. These simulations show that the intensity of delayed γ rays produced from competing reactions yields a precise measurement of the range of the proton beam relative to the marker, with sub-millimetre uncertainty.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".