Monte Carlo calculation of the TG-43 dosimetry parameters for the INTRABEAM source with spherical applicators
Bibliographic record
Abstract
OBJECTIVE: 245041). The current study focuses on the dosimetry characterization of the INTRABEAM source with the eight available spherical applicators according to the TG-43 formalism using Monte Carlo (MC) simulations. APPROACH: This report includes the calculated dose-rate conversion coefficients that determine the absolute dose rate to water at a reference point of 10 mm from the applicator surface, based on calibration air-kerma rate measurements at 50 cm from the source on its transverse plane. Since the air-kerma rate measurements are not yet provided from a standards laboratory for the INTRABEAM, the values in the present study were calculated with MC. This approach is aligned with other works in the search for standardization of the dosimetry of electronic brachytherapy sources. As a validation of the MC model, depth dose calculations along the source axis were compared with calibration data from the source manufacturer. MAIN RESULTS: The calculated dose-rate conversion coefficients were 434.0 for the bare probe, and 683.5, 548.3, 449.9, 376.5, 251.0, 225.6, 202.8, and 182.6 for the source with applicators of increasing diameter from 15 to 50 mm, respectively. The radial dose and the 2D anisotropy functions of the TG-43 formalism were also obtained and tabulated in this document. SIGNIFICANCE: This work presents the data required by a treatment planning system for the characterization of the INTRABEAM system in the context of intraoperative radiotherapy applications.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 0.001 |
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".