Comparing calibration methods of electron beams using plane‐parallel chambers with absorbed‐dose to water based protocols
Bibliographic record
Abstract
Recent absorbed-dose-based protocols allow for two methods of calibrating electron beams using plane-parallel chambers, one using the N(Co)D,w for a plane-parallel chamber, and the other relying on cross-calibration of the plane-parallel chamber in a high-energy electron beam against a cylindrical chamber which has an N(Co)D,w factor. The second method is recommended as it avoids problems associated with the Pwall correction factors at 60Co for plane-parallel chambers which are used in the determination of the beam quality conversion factors. In this article we investigate the consistency of these two methods for the PTW Roos, Scanditronics NACP02, and PTW Markus chambers. We processed our data using both the AAPM TG-51 and the IAEA TRS-398 protocols. Wall correction factors in 60Co beams and absorbed-dose beam quality conversion factors for 20 MeV electrons were derived for these chambers by cross-calibration against a cylindrical ionization chamber. Systematic differences of up to 1.6% were found between our values of Pwall and those from the Monte Carlo calculations underlying AAPM TG-51, and up to 0.6% when comparing with the IAEA TRS-398 protocol. The differences in Pwall translate directly into differences in the beam quality conversion factors in the respective protocols. The relatively large spread in the experimental data of Pwall, and consequently the absorbed-dose beam quality conversion factor, confirms the importance of the cross-calibration technique when using plane-parallel chambers for calibrating clinical electron beams. We confirmed that for well-guarded plane-parallel chambers, the fluence perturbation correction factor at d(max) is not significantly different from the value at d(ref). For the PTW Markus chamber the variation in the latter factor is consistent with published fits relating it to average energy at depth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".