Poster — Thur Eve — 27: Investigation of the Influence of Different Encapsulating Material on 170Tm Brachytherapy Source Spectra
Bibliographic record
Abstract
The purpose of this work was to investigate the influence of the encapsulating material on different part of the 170Tm decay spectra. A hypothetical 170Tm source with the Flexisource brachytherapy encapsulation was used in the simulations. The active core of the source is a pure thulium cylinder with a length of 3.5 mm, a radius of 0.3 mm and covered with a stainless‐steel or a pure gold cylinder. The length of the capsule is 5 mm, the inner radius is 3.0 mm and the outer radius 0.425 mm. Simulations were performed with and without taking the source encapsulation into account. The simulation utilized GEANT4 Monte Carlo code version 9.2. For the stainless‐steel encapsulation 95.5% of the total brems Strahlung is produced inside the core, 3.8% in the capsule and less than 1% in the water. For the gold capsule 85% is produced inside the core, 14.2% inside the gold capsule and negligible amount (<1%) in water. The range of the beta particles decreases with 1.1 mm with the stainless‐steel encapsulation but the tissue will still receive dose from the beta particles up to 3 mm from the source. The gold encapsulation, if present, absorbs most of the electrons and attenuates low energy photons. The mean energy of the photons escaping the core and the stainless‐steel capsule is 113 keV while for gold capsule the mean energy is 160 keV. TG43 parameters in both cases are extracted.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".