Monte Carlo calculated absorbed‐dose energy dependence of EBT3 and EBT4 films for 5–200 MeV electrons and 100 keV–15 MeV photons
Bibliographic record
Abstract
Abstract Purpose To use Monte Carlo simulations to study the absorbed‐dose energy dependence of GAFChromic EBT3 and EBT4 films for 5–200 MeV electron beams and 100 keV–15 MeV photon beams considering two film compositions: a previous EBT3 composition (Bekerat et al.) and the final composition of EBT3/current composition of EBT4 (Palmer et al.). Methods A water phantom was simulated with films at 5–50 mm depth in 5 mm intervals. The water phantom was irradiated with flat, monoenergetic 5–200 MeV electron beams and 100 and 150 keV kilovoltage and 1–15 MeV megavoltage photon beams and the dose to the active layer of the films was scored. Simulations were rerun with the films defined as water to compare the absorbed‐dose response of film to water, . Results For electrons, the Bekerat et al. composition had variations in of up to from 5 to 200 MeV. Similarly, the Palmer et al. composition had differences in up to from 5 to 200 MeV. For photons, varied up to and from 100 keV to 15 MeV for the Bekerat et al. and Palmer et al. compositions, respectively. The depth of films did not appear to significantly affect for photons at any energy and for electrons at energies 50 MeV. However, for 5 and 10 MeV electrons, decreases of up to in were seen due to stacked films and increased beam attenuation in films compared to water. Conclusions The up to and variations in for electrons and photons, respectively, across the energies considered in this study indicate the importance of calibrating films with the energy intended for measurement. Additionally, this work emphasizes potential issues with stacking films to measure depth dose curves, particularly for electron beams with energies 10 MeV.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".