Monte Carlo Modelling of an Orthovoltage X-ray System Using Multiple Applications in EGSnrc
Bibliographic record
Abstract
Biodosimetry relies on calibration curves to convert biological damage induced by ionizing radiation to an absorbed dose. Health Canada generates these curves by irradiating biological samples with X-rays, though exposures scenarios could consist of other types of radiation which are challenging to replicate in the laboratory. The ultimate goal of this work is to model the X-ray setup using Monte Carlo methods and to validate the model using inlaboratory measurements. The model was iterated through preliminary and final testing phases in different EGSnrc applications (egs++, SpekPy and BEAMnrc) and optimized using variance reduction techniques, resulting in multiple models. The X-ray spectra produced from each model were compared and found to be equivalent. Model outputs were also compared against laboratory measurements to identify the most accurate model. The final model output will be used in the next phase of the project to model radiobiological damage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".