SU‐C‐105‐07: A New Criterion for Detector Usability in Nonstandard Beam Dosimetry
Bibliographic record
Abstract
Purpose: To accurately convert the detector signal to absorbed dose to water in nonstandard beams, beam quality correction factors (kQ) are required. To avoid calculating such factors, we define a criterion based on the hypothesis that, for a given detector, kQ is unity within a given tolerance. This allows establishing detector‐specific critical regions to limit the field sizes usable experimentally without the need for evaluating kQ. Methods: A theoretical relation between the relative deviation of kQ from unity and a function that depends on dose response kernels is derived. Kernels are computed using the Monte Carlo user code egs_chamber for water and for three different ionization chambers (Exradin A12, A14 and A1SL), simulating 6 MV photon pencil beams at several lateral positions. Critical regions around the centroid of the chambers that guarantee kQ to remain within +/−0.005 from unity are obtained. For field sizes equal to the critical regions, kQ factors are calculated to validate the theoretical approach. Results: To limit kQ within +/−0.005 from unity, field sizes were determined to be 2.6× 5.2 cm2 for the A12, 3.8 × 3.8 cm2 for the A14 and 2.5 × 2.9 cm2 for the A1SL chamber. The corresponding kQ were found to be 1.0019 +/− 0.0026 for the A12, 1.0001 +/− 0.0047 for the A14 and 1.0011 +/− 0.0024 for the A1SL. These results are found within the expected deviation and fully support the validity of the new criterion. Conclusion: In this study, the limitation of the field size to a detector‐specific critical region allows small beam measurements to be done without the need for evaluating kQ factors. While this work will be extended to other types of detectors, the methodology will serve as a basis to study IMRT beams in the scope of new dosimetry protocols.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".