TU‐E‐224A‐02: Dosimetry of Very Small (1.5 and 3 Mm Diameter) Photon Beams: Diode and Film Measurements Versus Monte Carlo Calculations
Bibliographic record
Abstract
Purpose: To measure the dosimetric parameters of 10 MV photon beams in 1.5 and 3 mm diameter fields with a small‐field diode, radiographic XV film, and radiochromic HS film, and to compare measured data with the same parameters calculated by Monte Carlo (MC) simulations. Methods and Materials: A 10‐MV Clinac‐18 linac was used as the radiation source and the very small diameter fields were set up with radiosurgical collimators. PDDs, profiles, and output factors of the very small photon beams were measured with diode/water tank and film/scanner techniques. The measured parameters were compared against those calculated by MC simulations using an experimentally determined circular source diameter of 1.5 mm in beam modeling. For improved accuracy, the PDDs were measured with the diode and the water tank using beam profile scans. A document scanner was used as film densitometer to offer high spatial resolution (254 lpi) required in very small photon field dosimetry. Results: PDDs measured by the diode agree well with the MC‐calculated results, within ± 2% and ± 3% in 3 and 1.5 mm fields, respectively. Lateral profiles measured by the diode and film generally agree with MC calculations, but significant discrepancies are observed in the tail portion of the 1.5‐mm beam profile. Relative dose factors obtained by averaging the diode, HS film, and MC results are 0.22 ± 0.01 and 0.43 ± 0.01 for the 1.5 and 3 mm fields, respectively. Conclusion: Based on the good agreement between the measured and MC‐calculated dosimetric parameters for the 1.5 and 3 mm diameter, 10 MV beams, we conclude that MC calculations can be used in general for dosimetry of very small photon fields, provided that the physical source size of the linac is correctly measured and used in the MC simulations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".