Influence of monitor chamber calibration on Virtual Wedge™ dosimetrya)
Bibliographic record
Abstract
We have investigated the influence of the linear accelerator (LINAC) monitor chamber calibration on the dosimetry of Siemens Virtual Wedge (VW.) The doses delivered in the three phases of wedge delivery (initial gap, sweep portion, and open field) utilize the ionization current generated in two dose monitoring ion chambers (MONITOR 1 and MONITOR 2) in the LINAC to control the wedge delivery. We intentionally offset the calibration of each of these chambers by +/- 3% and observed up to a 13% change in the dose along the wedge profile for a 6 MV beam at a field size of 20 x 20 cm2. If the calibration of one of the two dose monitoring chambers changed independently then the relative dose at points along the wedge profile were affected. Furthermore, the percentage change in dose varied across the wedge profile thereby affecting the wedge angle as well as the central axis wedge factor. We also present equations for calculating the change in dose at a position along the wedge profile as a function of monitor chamber calibration. A comparison with measurement showed that our theoretical predictions were accurate to within +/- 1.7%. The equations have proven useful tools in evaluating periodic drifts in VW dosimetry.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".