Difference in the relative response of the alanine dosimeter to megavoltage x-ray and electron beams
Bibliographic record
Abstract
In order to increase the usefulness of the alanine dosimeter as a tool for quality assurance measurements in radiotherapy using MV x-rays, the response with respect to the dose to water needs to be known accurately. This quantity is determined experimentally relative to (60)Co for 4, 6, 8, 10, 15 and 25 MV x-rays from two clinical accelerators. For the calibration, kQ factors for ionization chambers with an uncertainty of 0.31% obtained from calorimetric measurements were used. The results, although not inconsistent with a constant difference in response for all MV x-ray qualities compared to (60)Co, suggest a slow decrease from approximately 0.996 at low energies (4-6 MV) to 0.989 at the highest energy, 25 MV. The relative uncertainty achieved for the relative response varies between 0.35% and 0.41%. The results are confirmed by revised experimental data from the NRC as well as by Monte Carlo simulations using a density correction for crystalline alanine. By comparison with simulated and measured data, also for MeV electrons, it is demonstrated that the weak energy dependence can be explained by a transition of the alanine dosimeter (with increasing MV values) from a photon detector to an electron detector. An in-depth description of the calculation of the results and the corresponding uncertainty components is presented in an appendix for the interested reader. With respect to previous publications, the uncertainty budget had to be modified due to new evidence and to changes of the measurement and analysis method used at PTB for alanine/ESR.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".