Sci—Sat AM: Brachy — 07: Plastic scintillation detector validation for kV dosimetry
Bibliographic record
Abstract
PURPOSE: To characterize the plastic scintillation detectors (PSDs) response in the diagnostic energy range. A fast and adaptable method for real-time dosimetry in superficial x-ray therapy and interventional radiology is proposed. METHOD: A PSD (1 mm diameter and 10 mm long) is coupled to a 5 m long optical fiber. Scintillation photons are guided to a polychromatic photodiode which provides an electrical current proportional to the input light signal. If the incident energy spectrum is known, the dose measured in the PSD's polystyrene sensitive volume can be converted to score dose in any other media such as air, water or soft tissues using the large cavity theory (LCT). A software simulating x-ray tube spectra and filtration has been benchmarked and is used for analysis. The method is confirmed by Monte Carlo simulations. RESULTS: PSDs cannot be assumed energy independent with low-energy photons as a factor 2 has been observed in the energy response between 80 kVp and 150 kVp. When the dose is converted to the desired medium, the PSD's energy dependence is compensated and a 2.1% standard deviation was observed upon the studied energy ranges, which is inside the measurement and calculation uncertainties. Percent depth dose (PDD) measurements are in good agreement with Monte Carlo simulations and results can be improved if the proposed method is applied to compensate beam hardening. CONCLUSION: PSDs present great potential for real-time dose measurements with radiologic photon energy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".