Dosimetric characterization of an accessory mounted mini-beam collimator across clinically beam matched medical linear accelerators
Bibliographic record
Abstract
Abstract Background and Purpose. The goal of this project was the dosimetric characterization of a mini-beam collimator across three clinically beam matched medical linear accelerators (linacs). Methods and Materials. The beam quality (%DD(10)), peak-to-valley dose ratio (PVDR), collimator factor ( C F f m i n i w ) , and relative output ( O F f m i n i w ) were obtained for 6 MV mini-beam collimated fields of various sizes on three clinically beam matched Varian iX medical linear accelerators. Monte Carlo simulations of the mini-beam collimated fields were used to correlate the experimental results to the accelerators’ electron beam full width-half maximum (FWHM) incident on the Bremsstrahlung target. Results. The beam quality of the mini-beam collimated field on all three linear accelerators agreed with that of the open field beam to within ±1%. PVDR on the different linacs varied by up to ±8.1% from the mean. Similarly, the collimator factors varied from the mean by up to ±3.6%. However, changes in the mini-beam collimated field due to changes in collimator inclination with respect to the beam central axis or field size were consistent across the three linacs. The collimator factors of the linacs were found to decrease by up to 7.1% in response to changes in inclination of less than 0.1°, and have an inverse relationship to field size. Monte Carlo simulations indicated that the disagreement in collimator factor can be linked to variation in the spatial width of the electron beam incident on the Bremsstrahlung target. Conclusion. A mini-beam collimator has been dosimetrically characterized on three clinically beam matched medical linear accelerators. Discrepancies in the mini-beam collimated field characteristics were observed across accelerators. Monte Carlo simulation revealed that these differences were related to the linac electron beam FWHM.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".