An experimental and Monte Carlo investigation of the energy dependence of alanine/EPR dosimetry: II. Clinical electron beams
Bibliographic record
Abstract
The energy dependence of alanine/EPR dosimetry for 8, 12, 18 and 22 MeV clinical electron beams was investigated by experiment and by Monte Carlo simulations. Alanine pellets in a waterproof holder were irradiated in a water phantom using an Elekta Precise linear accelerator. The dose rates at the reference point were determined following the TG-51 protocol using an NACP-02 parallel-plate chamber calibrated in a (60)Co beam. The EPR spectra of irradiated pellets were measured using a Bruker EMX 081 EPR spectrometer. Experimentally, we found no significant change in alanine/EPR response to absorbed dose-to-water over the energy range 8-22 MeV at an uncertainty level of 0.6%. However, the response for high-energy electrons is about 1.3 (+/-1.1)% lower than for (60)Co. The EGSnrc Monte Carlo system was used to calculate the ratio of absorbed dose-to-alanine to absorbed dose-to-water and it was shown that there is 1.3 (+/-0.2)% reduction in this ratio from the (60)Co beam to the electron beams, which confirms the experimental results. Alanine/EPR response per unit absorbed dose-to-alanine was also investigated and it is the same for high-energy electrons and (60)Co gamma-rays.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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".