Relative effectiveness of polyacrylamide gel dosimeters applied to proton beams: Fourier transform Raman observations and track structure calculations
Bibliographic record
Abstract
The feasibility of using polyacrylamide gel (PAG) to characterize a clinically relevant 74 MeV proton beam has been considered. Fourier transform Raman spectroscopy has been used to measure the response (i.e., consumption of monomer) of PAG exposed to the central and end portions of a spread out Bragg peak (SOBP), i.e., in two regions with measurable difference in proton linear energy transfer (LET). The response curve in each region was compared with a typical 6 MV x-ray irradiated gel response curve, thus arriving at a gel "relative effectiveness" (RE) in each of the two regions. In addition, the theory of track structure, which is typically used to calculate a detector RE, is shown to give reasonable agreement when compared with the experimental results. Both experimental and track structure results indicate a decrease in gel response when irradiated with protons, as compared with the x-ray response. In addition, both sets of results indicate a variation in gel response between the mid and end SOBP regions, thus illuminating the dependence of gel response to proton LET. The physical phenomenon causing a lower proton versus x-ray gel response may be understood by considering the track structure calculations, which indicate that gel radiosensitive elements close to the track of a proton (i.e., within 1.5 x 10(-6) cm) are saturated. This saturation is due to the high delta-ray doses deposited in these regions. The track calculations are extended to other situations (e.g., raw BP, different gel compositions) where experimental determination of RE is difficult or time consuming. Results again indicate a gel response dependent on position in the depth dose curve (i.e., LET). Overall, this study illuminates the difficulty in using polyacrylamide gel to extract quantitative dose maps when exposed to proton radiation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".