Development and application of a water calorimeter for the absolute dosimetry of short-range particle beams
Bibliographic record
Abstract
Abstract In this work, we describe a new design of water calorimeter built to measure absorbed dose in non-standard radiation fields with reference depths in the range of 6–20 mm, and its initial testing in clinical electron and proton beams. A functioning calorimeter prototype with a total water equivalent thickness of less than 30 mm was constructed in-house and used to obtain measurements in clinical accelerator-based 6 MeV and 8 MeV electron beams and cyclotron-based 60 MeV monoenergetic and modulated proton beams. Corrections for the conductive heat transfer due to dose gradients and non-water materials was also accounted for using a commercial finite element method software package. Absorbed dose to water was measured with an associated type A standard uncertainty of approximately 0.4% and 0.2% for the electron and proton beam experiments, respectively. In terms of thermal stability, drifts were on the order of a couple of hundred µ K min −1 , with a short-term variation of 5–10 µ K. Heat transfer correction factors ranged between 1.021 and 1.049. The overall combined standard uncertainty on the absorbed dose to water was estimated to be 0.6% for the 6 MeV and 8 MeV electron beams, as well as for the 60 MeV monoenergetic protons, and 0.7% for the modulated 60 MeV proton beam. This study establishes the feasibility of developing an absorbed dose transfer standard for short-range clinical electrons and protons and forms the basis for a transportable dose standard for direct calibration of ionization chambers in the user’s beam. The largest contributions to the combined standard uncertainty were the positioning (⩽0.5%) and the correction due to conductive heat transfer (⩽0.4%). This is the first time that water calorimetry has been used in such a low energy proton beam.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".