Relative response of alanine dosemeters for high-energy electrons determined using a Fricke primary standard
Bibliographic record
Abstract
A significant proportion of cancer patients is treated using MeV electron radiation. One of the measurement methods which is likely to furnish reliable dose values also under non-reference conditions is the dosimetry using alanine and read-out via electron spin resonance (ESR). The system has already proven to be suitable for QA purposes for modern radiotherapy involving megavoltage x-rays. In order to render the secondary standard measurement system of the Physikalisch-Technische Bundesanstalt based on alanine/ESR useable for dosimetry in radiotherapy, the dose-to-water (D(W)) response of the dosemeter needs to be known for relevant radiation qualities. For MeV electrons, the D(W) response was determined using the Fricke primary standard of the Swiss Federal Office of Metrology. Since there were no citable detailed publications on the Swiss primary standard available, this measurement system is described in some detail. The experimental results for the D(W) response are compared to results of Monte Carlo simulations which model in detail the beams furnished by the electron accelerator as well as the geometry of the detectors. The agreement between experiment and simulation is very good, as well as the agreement with results published by the National Research Council of Canada which are based on a different primary standard. No significant dependence of the D(W) response was found in the range between 6 and 20 MeV. It is therefore suggested to use a unique correction factor k(E) for alanine for all MeV qualities of k(E) = 1.012 ± 0.010.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".