TH‐C‐BRB‐08: Improving Reference Dosimetry of Nonstandard Beams
Bibliographic record
Abstract
Purpose: First to characterize the factors responsible for non‐unity corrections in nonstandard beam dosimetry and provide conceptual solutions to minimize corrections. Second to provide methods to estimate uncertainties accurately in nonstandard beam dosimetry and achievable levels in clinical situations. Materials: Ionization chamber response to static and dynamic IMRT deliveries is simulated using Monte Carlo and chamber perturbation factors are calculated. An exhaustive characterization and uncertainty analysis method applied to radiochromic film dosimetry is performed. Experimental criteria for achieving required levels of uncertainties are predicted using the method. An implementation of a Monte Carlo based setup positioning‐induced dose uncertainty (PIDU) is performed in egs_chamber to evaluate uncertainties during ionization chamber measurements. An Exradin A12 chamber and a PTW 60012 diode models are used to numerically evaluate PIDU in nonstandard beams. Results: Results show that the factor responsible for large corrections factors in nonstandard beams is the gradient effect. Reporting dose to the sensitive volume of the chamber filled with water reduces the correction factor by half under high gradients. A theoretical expression of correction factors is obtained for ideal nonstandard reference fields. Levels of uncertainty of the order of 0.3% are achieved with strict procedures of radiochromic film dosimetry and show great potential for non‐standard beam measurements. Realistic uncertainties up to 4% on IMRT kQ factor measurements are reported using the Exradin A12 in modulated fields. Realistic uncertainties up to 3% using a PTW 60012 diode are reported for small beam output factor measurements. Conclusions: Reporting dose to the volume of the chamber instead of a point of measurement could reduce the correction factors. Depending on outcomes of future developments corrections could be eliminated. Uncertainties in non‐standard beams are an important issue during QA routine and reference dosimetry and could be a limiting factor in the new protocol generation.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".