Evaluation of radiochromic formulations for dosimetry in high-energy photon and proton beams
Bibliographic record
Abstract
Radiochromic crystals have many suitable features for dosimetry across a broad range of radiotherapy modalities, yet the study of these materials within the medical physics community has been limited. Here, we study three types of radiochromic pentacosa-10,12-diynoic acid-based formulations: two analogues of commercially available materials and one newly developed. Formulations coated on polyethylene are irradiated with photon (6 and 10 MV) and proton (74 MeV) beams (0–25 Gy) using custom fibre-optic setups that enable real-time transmission measurements at 1.5–2 cm depth to maintain dosimetric accuracy. The dose response to ionizing radiation is compared between the formulations and all formulations were characterized using a variety of analytical methods. The response of radiochromic crystals to ionizing radiation is complex and influenced by factors such as monomer composition and resulting macroscopic crystal morphology. By optimizing these parameters, it could be possible to develop dosimeters suitable for a variety of clinical applications. Even though radiochromic crystals are promising for dosimetry in diverse radiotherapy modalities, and their response can be optimized through monomer composition, exploration of these materials in this context remains limited. Here, three pentacosa-12,12-diynoic acid-based formulations are studied
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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 | 0.000 | 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 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".