SU‐GG‐T‐327: Measurement of Small Field Output Factors Using Plastic Scintillation Detectors
Bibliographic record
Abstract
Purpose: To investigate the performance of a small volume, water‐equivalent plastic scintillation detector (PSD) for measuring output factors for small IMRT fields, as compared to 0.01cm3 ionization chamber. Method and Materials: A PSD of 0.5 mm diameter and 2 mm length was irradiated with 6 and 18 MV beams from a Varian Clinac 21EX. The PSD was positioned vertically at a source‐to‐axis distance of 100 cm, at 10 cm depth in a water phantom, and irradiated with fields ranging in size from 0.5 × 0.5 cm2 to 10 × 10 cm2. The field sizes were defined either by the collimator jaws alone, or by a multi‐leaf collimator (MLC) alone. The MLC fields were constructed in two ways: with the closed leaves (i.e., those leaves that were not opened to define the square field) meeting at either the field center‐line, or at a 4 cm offset from center‐line. Scintillation light was recorded using a CCD camera. Measurements were made using a CC01 ionization chamber under conditions identical to those used for the PSD. Results: Output factors measured using the PSD were found to be in good agreement with those measured using the CC01 down to a field size of 2.0 × 2.0 cm2. The PSD measured higher output factors than the CC01 at smaller fields, e.g. by 7.8 % at 0.5 × 0.5 cm2 under 6 MV photons using MLC fields with 4 cm leaf offset. Also, output factors were found to depend on the field defining geometry. Conclusion: This study suggests that PSDs provide a useful alternative to existing dosimetry systems for small fields, as they are less susceptible to volume averaging and perturbation effects than larger, air‐filled ionization chambers. Therefore, PSDs may provide more accurate output factor determination due to their inherent properties. Supported by the NCI 1R01CA120198‐01A2.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".