Sci-Fri AM(2): Brachy-06: The NRC Electron Beam Primary Standard Water Calorimeter
Bibliographic record
Abstract
Introduction Electron dosimetry, for the majority of clinical dose measurements worldwide, is currently based on an ion chamber calibrated at the standards laboratory in a beam. Conversion factors obtained from a protocol such as AAPM TG-51 are then required to derive the dose in a linac electron beam. Electron beam water calorimetry offers a direct method to calibrate ion chambers in the clinical beams that they will be used in. This presentation details the development of a primary standard water calorimeter at the National Research Council in Ottawa and the method to calibrate ion chambers. Materials and Method The calorimeter is based on the NRC absorbed dose primary standard but the design is optimized for use in electron beams down to 8 MeV. After validation of the design the calorimeter was used to calibrate a set of cylindrical and parallel-plate chambers (NE2571, NACP-02, PTW Roos) in 12, 18 and 22 MeV electron beams from an Elekta Precise linac. Results The values obtained were compared to those obtained using TG-51 and found to agree at the 1% level. The measured energy dependence of ion chamber calibrations was compared with data from three other laboratories that have developed electron beam standards and agreement generally better than 1% was obtained there. The standard uncertainty in the calibration of an ion chamber is estimated to be 0.35%, which will give significant improvement in the measured dose uncertainty compared to using protocol-based values.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.038 | 0.017 |
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".