Poster - Thurs Eve-24: Dosimetry study on the penumbra region for the irregular MLC fields with stepping patterns
Bibliographic record
Abstract
The aim of this study is to investigate the dosimetric effect in the penumbra region for the multi-leaf collimator (MLC) fields with stepping patterns. Various irregular MLC fields with different stepping patterns were designed. Radiographic films were used to measure the beam profiles (cross-plane (X1-X2 jaw) and in-plane (Y1-Y2 jaw)) for different MLC field configurations of varying lengths of protruded leaves adjacent (on one or both sides) to the beam profile axis. 6 MV photon beams produced by the Varian 21 EX linear accelerator with 120-leaf Millennium MLC were used. The results showed that the penumbra widths (10% - 90%) of the profiles (cross-plane) with 0.5 cm gap width increased with the protruded lengths of the neighbouring leaves, while the penumbra widths did not vary too much for the larger gap widths of 1 cm and 1.5 cm. The neighbouring leaf's influence on the profile was very insignificant, when the distance between the profile and neighbouring leaf edge was larger than 1 cm. Moreover, when both the upper and lower portions of leaves were moved out forming a gap for the profile, the dose at the "edge" region was decreased by about 20% and 6% when the protruded lengths of the leaves were 0.5 cm and 1 cm, respectively. It is important to understand the dosimetric effect in the penumbra region for irregular MLC fields with stepping leaf patterns, especially during the commissioning process for the conformal external beam and intensity modulated radiation therapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.004 | 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".