Solid Water as phantom material for dosimetry of electron backscatter using low‐energy electron beams: A Monte Carlo evaluation
Bibliographic record
Abstract
This study evaluated the dosimetry of electron backscatter when Solid Water is used to substitute water as phantom in electron radiotherapy. Monte Carlo simulation (EGSnrc-based code) was employed to predict electron energy spectra and depth doses for the 0.5 and 1 cm of Solid Water and water slabs above 3 mm of lead (Pb) layers using electron beams with energies of 4 and 6 MeV. For comparison, Monte Carlo simulations were repeated with Pb layers taken out from the phantoms using the same experimental configuration. Analyses on electron energy spectra for the 4 and 6 MeV electron beams showed that deviations of electron energy distributions between the Solid Water and water phantom were more significant in the high-energy range (i.e., close to the maximal electron energy) than the lower range corresponding to the electron backscatter. These deviations of electron energy spectra varied with depth and were mainly due to the electron fluence or beam attenuation. Dosimetry results from Monte Carlo simulations showed that the Solid Water phantom had lower depth dose compared to water with the same experimental setup. For the 4 MeV electron beams with 0.5 cm of Solid Water, depth doses were 1.8%-3.9% and 2.3%-4.4% lower than those in water, with and without the Pb layer underneath, respectively. Thicker Solid Water of 1 cm resulted in different decreases in depth doses of 1.8%-4.6% (with Pb) and 2.3%-4.4% (without Pb) compared to water. For higher nominal electron beam energy of 6 MeV with 0.5 cm of Solid Water, depth doses decreased 1.7%-2.9% (with Pb) and 1.6%-2.1% (without Pb) compared to water. These decreases in depth doses changed to 1.7%-3.7% (with Pb) and 1.7%-3% (without Pb) when the thickness of Solid Water was increased to 1 cm. The dosimetry data in this study are useful in determining the correction factor when using Solid Water to substitute water for the electron backscatter measurement in electron radiotherapy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".