Dosimetric characterization of an intensity-modulated X-ray brachytherapy system
Bibliographic record
Abstract
PURPOSE: An intensity-modulated X-ray brachytherapy system is being developed for various clinical applications. This new system makes it possible for clinical staff to control energy as well as dose rate for different tumor sites according to their sizes and radiobiological characteristics. MATERIALS AND METHODS: This system is mainly composed of an X-ray tube, guide tube collimation, and secondary (pseudo) target. Due to its configuration, convenient modulations of fluorescent X-ray energy and intensity are possible. To observe applicability of this novel system for various primary and secondary target combinations, Monte Carlo simulation using MCNP5 was performed, and air measurements were done. As a primary and pseudo-target combination, silver-molybdenum (Ag-Mo), tungsten-neodymium (W-Nd), and tungsten-erbium (W-Er) were used for the calculation for dose profile. Specifically, a dose distribution was calculated around each of these target combinations. Dose distributions as a function of target angles were also calculated. The Ag-Mo combination was analyzed for Cartesian coordinates of xy, xz, and yz planes of the pseudo-target to observe dose distribution as a function of the angle of secondary target. RESULTS: I) due to its low characteristic X-ray energy. CONCLUSIONS: Dose distribution variance should be considered in beam modulation for clinical application. Dynamic movement of the pseudo-target is feasible and remains as a subject for future research.
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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 | 0.000 |
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".