Determination of <i>W</i><sub>air</sub> in high‐energy electron beams using graphite detectors
Bibliographic record
Abstract
Purpose ICRU Report 90 on Key Data for Ionizing‐Radiation Dosimetry: Measurement Standards and Applications (2014) has reaffirmed the recommended value of the mean energy required to create an ion pair in air, Wair, to be 33.97(12) eV. The report also indicates that this “constant” of radiation dosimetry is energy independent above 10 keV, since there is no theoretical or experimental evidence to the contrary. The goal of this investigation is to obtain additional experimental determinations of Wair in high energy beams and thus to verify the suggested energy independence. Methods Wair can be evaluated by combining ionometric and calorimetric measurements with a calculated ratio of the absorbed dose in the ion chamber air cavity and that of the calorimeter absorbing element. In this investigation, a graphite parallel plate chamber and a graphite calorimeter were used and the dose ratio was calculated using the EGSnrc Monte Carlo code. Measurements were made in electron beams from the NRC Vickers linear accelerator at two incident energies, 20 and 35 MeV. A range of average energies at the measurement point were obtained by inserting graphite plates in the primary beam. Results The average value of Wair obtained in this investigation is 33.85(18) eV which is consistent with the recommended value of 33.97(12) eV where the number in brackets represents the combined standard uncertainty of the value, referring to the corresponding last digits. The individual values of Wair do not show any statistically significant energy dependence. Conclusion The overall combined uncertainty of 0.5% meets the original target of the investigation. A larger‐scale investigation, involving more individual energy points and a wider range of electron energies is required to go further and, for example, comment on the Wair energy dependency question raised by Tessier et al. [Med. Phys. 2018;45:370–381].
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".