TH‐D‐224C‐07: Focal Source Size Measurement for Monte Carlo Simulations of Percentage Depth Doses in Very Small Photon Fields
Bibliographic record
Abstract
Purpose: To measure the focal spot of a 10‐MV Clinac‐18 linac for use in Monte Carlo (MC) calculation of percentage depth doses (PDDs) in a very small (1.5 mm diameter) field. Methods and Materials: A technique using a translational slit‐assembly system was developed to measure the linac focal spot. The assembly consists of two lead blocks fastened together to produce a 300 μm wide slit. A small field diode was centered below the slit, reading radiation signals transmitted through the slit while the system (mounted at a distance of 65 cm from the target) was translated linearly across an open beam. The linear translation was achieved through a screw driving mechanism and the position of the slit was measured with a digital caliper. The source dimension was estimated from the FWHM of the Gaussian fit to scanned profiles corrected for background transmission signal. Results: Scans in various angular orientations perpendicular to the beam central axis show that the linac focal spot is elliptical with principal axes of (1.1 ± 0.1) mm and (2.1 ± 0.1) mm. Isodose distribution measured on the solid water phantom surface in a plane perpendicular to the beam central axis for the 1.5‐mm diameter, 10 MV photon beam is also elliptical and oriented in accordance with the measured source shape. A circular Gaussian source model with a FWHM of 1.5 mm, approximating the measured focal spot, was used in the MC calculation of PDDs for the 1.5 mm beam. The MC‐calculated PDDs agree within 2% with measured data. Conclusions: In contrast to standard radiotherapy fields, MC‐calculated PDDs for very small fields show a strong dependence on source dimension. The good agreement between the measured and MC‐calculated PDDs for the 1.5 mm diameter 10 MV beam validates the MC simulation technique using appropriate focal source size.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".