Theoretical and experimental characterization of novel water-equivalent plastics in clinical high-energy carbon-ion beams
Bibliographic record
Abstract
Water-equivalent plastics are frequently used in dosimetry for experimental simplicity. This work evaluates the water-equivalence of novel water-equivalent plastics specifically designed for light-ion beams, as well as commercially available plastics in a clinical high-energy carbon-ion beam. A plastic- to-water conversion factor was established to derive absorbed dose to water in a water phantom from ionization chamber readings performed in a plastic phantom. Three trial plastic materials with varying atomic compositions were produced and experimentally characterized in a high-energy carbon-ion beam. Measurements were performed with a Roos ionization chamber, using a broad un-modulated beam of 11 × 11 cm 2 , to measure the plastic-to-water conversion factor for the novel materials. The experimental results were compared with Monte Carlo simulations. Commercially available plastics were also simulated for comparison with the plastics tested experimentally, with particular attention to the influence of nuclear interaction cross sections. The measured correction increased gradually from 0% at the surface to 0.7% at a depth near the Bragg peak for one of the plastics prepared in this work, while for the other two plastics a maximum correction of 0.8%–1.3% was found. Average differences between experimental and numerical simulations were 0.2%. Monte Carlo results showed that for polyethylene, polystyrene, Rando phantom soft tissue and A-150, the correction increased from 0% to 2.5%–4.0% with depth, while for PMMA it increased to 2%. Water-equivalent plastics such as, Plastic Water, RMI-457, Gammex 457-CTG, WT1 and Virtual Water, gave similar results where maximum corrections were of the order of 2%. Considering the results from Monte Carlo simulations, one of the novel plastics was found to be superior in comparison with the plastic materials currently used in dosimetry, demonstrating that it is feasible to tailor plastic materials to be water-equivalent for carbon ions specifically.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".