WE‐C‐BRB‐03: Effect of Scattered Photons When Determining Dose Rate Constants Spectroscopically
Bibliographic record
Abstract
Purpose: To determine the effect of scatter from the seed when establishing the dose rate constant of 125I and 103Pd seeds using the spectroscopic method of Chen and Nath (Med Phys 34 (2007) 1412) which is based on the main peaks in the spectrum. Methods: The energy spectra generated by two 125I and one 103Pd seeds were calculated in vacuo at 10 cm from the source using the EGSnrc BrachyDose Monte Carlo code. Energy bin width was 0.2 keV and statistical uncertainty was 0.02%. The energy spectra generated by the seeds were then used as a 3 mm line source in a Monte Carlo simulation to calculate the dose rate constant. Two simulation were performed; one using the full energy spectrum and the other using only the main peaks. Statistical uncertainty in air kerma strength and dose rate was 0.1%. Results: The differences between the average energy of the full spectrum and the average energy of the main peaks generated by the three seeds were 0.07% or less. Differences in air kerma strength and dose rate constant were 0.5% or less and the difference in the dose rate was lower than the statistical uncertainty (0.1%). Conclusions: Air kerma strength, dose rate at the reference point and dose rate constant were calculated by Monte Carlo simulation using both the full energy spectrum and the main peaks only of three brachytherapy seeds. The differences in the calculation of these clinical parameters were less than 0.5%. This difference is substantially lower than the reported uncertainty in establishing the dose rate constant spectroscopically, which can reach up to 3.9% and 2.6% for the 125I and 103Pd seeds respectively. Therefore, the effects of scatter on determining the dose rate constant spectroscopically is absorbed by the other uncertainties in the method.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".