Sci-Thur PM: YIS - 07: Monte Carlo simulations to obtain several parameters required for electron beam dosimetry
Bibliographic record
Abstract
When current dosimetry protocols were written, electron beam data were limited and had uncertainties that were unacceptable for reference dosimetry. Protocols for high-energy reference dosimetry are currently being updated leading to considerable interest in accurate electron beam data. To this end, Monte Carlo simulations using the EGSnrc user-code egs_chamber are performed to extract relevant data for reference beam dosimetry. Calculations of the absorbed dose to water and the absorbed dose to the gas in realistic ion chamber models are performed as a function of depth in water for cobalt-60 and high-energy electron beams between 4 and 22 MeV. These calculations are used to extract several of the parameters required for electron beam dosimetry — the beam quality specifier, R50, beam quality conversion factors, kQ and kR50, the electron quality conversion factor, k′R50, the photon-electron conversion factor, kecal, and ion chamber perturbation factors, PQ. The method used has the advantage that many important parameters can be extracted as a function of depth instead of determination at only the reference depth as has typically been done. Results obtained here are in good agreement with measured and other calculated results. The photon-electron conversion factors obtained for a Farmer-type NE2571 and plane-parallel PTW Roos, IBA NACP-02 and Exradin A11 chambers are 0.903, 0.896, 0.894 and 0.906, respectively. These typically differ by less than 0.7% from the contentious TG-51 values but have much smaller systematic uncertainties. These results are valuable for reference dosimetry of high-energy electron beams.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".