An experimental and Monte Carlo investigation of the energy dependence of alanine/EPR dosimetry: I. Clinical x-ray beams
Bibliographic record
Abstract
The energy dependence of alanine/EPR dosimetry, in terms of absorbed dose-to-water for clinical 6, 10, 25 MV x-rays and 60Co gamma-rays was investigated by measurements and Monte Carlo (MC) calculations. The dose rates were traceable to the NRC primary standard for absorbed dose, a sealed water calorimetry. The electron paramagnetic resonance (EPR) spectra of irradiated pellets were measured using a Bruker EMX 081 EPR spectrometer. The DOSRZnrc Monte Carlo code of the EGSnrc system was used to simulate the experimental conditions with BEAM code calculated input spectra of x-rays and gamma-rays. Within the experimental uncertainty of 0.5%, the alanine EPR response to absorbed dose-to-water for x-rays was not dependent on beam quality from 6 MV to 25 MV, but on average, it was about 0.6% lower than its response to 60Co gamma-rays. Combining experimental data with Monte Carlo calculations, it is found that the alanine/EPR response per unit absorbed dose-to-alanine is the same for clinical x-rays and 60Co gamma-rays within the uncertainty of 0.6%. Monte Carlo simulations showed that neither the presence of PMMA holder nor varying the dosimeter thickness between 1 mm and 5 mm has significant effect of the energy dependence of alanine/EPR dosimetry within the calculation uncertainty of 0.3%.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".