An <scp>EGS</scp>nrc investigation of cavity theory for ion chambers measuring air kerma
Bibliographic record
Abstract
The EGSnrc system is used to compare the response of an aluminum-walled thimble chamber to that of a graphite-walled thimble chamber for a 60Co beam. When compared to previous experimental results, the EGSnrc values of the ratios of chamber response differ by as much as 0.7% from the experiment. However, it is shown that this difference can be more than accounted for by switching from using the graphite mean excitation energy of 78 eV used in dosimetry protocols to the value of 86.8 eV suggested by more recent stopping-power experiments. This suggests that the uncertainty analysis of Monte Carlo results must be done more carefully, by taking into account uncertainties in the underlying basic data such as the electron and photon cross sections. In comparison to Spencer-Attix cavity theory for a thick-walled ion chamber, the Monte Carlo calculated values of the chamber response differ from the expected ones by 0.15% and 0.01% for the graphite and aluminum chambers, respectively, which are comparable to previously reported values for the Spencer-Attix correction factors. EGSnrc is also used to investigate the effect on the chamber response of thin dag layers on the inside of the aluminum wall. There is good agreement between the calculated and measured changes in chamber response versus the thickness of the dag. The results are compared to the predictions of the Almond-Svensson extension of cavity theory and show that the theory does not correctly predict the chamber response in the presence of thin dag layers. This finding is in agreement with previously reported experimental results. It is demonstrated that the values of alpha, the fraction of ionizations in the gas arising from electrons generated in the dag layer, used in the theory, are not the source of the disagreement.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".