Sci‐YIS Fri ‐ 02: Calculated P<sub>wall</sub> values in clinical photon beams
Bibliographic record
Abstract
Dosimetry of high‐energy photon beams is based upon absorbed dose to water standards and requires the use of ionization chambers with several correction factors. This study investigates the wall correction factor, Pwall, in high‐energy photon beams for both cylindrical and parallel‐plate chambers using Monte Carlo calculations. For cylindrical chambers, dosimetry protocols use an empirical formula to determine Pwall despite high quality experimental evidence that there are problems with this formula. Wall corrections are not provided for parallel‐plate chambers in photon beams due to a lack of information available regarding the correction factors for these chambers. Monte Carlo calculations are carried out using the EGSnrc user‐code CSnrc to calculate the wall correction factor for a series of ion chambers using a correlated sampling variance reduction technique. Calculations of the wall correction are performed for a variety of chambers at the reference depth in photon beams, using realistic beam spectra from clinical accelerators, ranging in nominal energy from to 24 MV. For cylindrical chambers, Pwall values differ by as much as 0.8% from the predicted values. This discrepancy is used to resolve previous experimental results that pointed to problems with the Pwall formalism. Pwall values are also shown for parallel‐plate chambers in high‐energy photon beams and have corrections up to 2%. These data should allow parallel‐plate chambers to be used in photon as well as in electron beams.
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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 | 0.004 |
| 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) | 0.003 | 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".