Absorbed dose to water reference dosimetry using solid phantoms in the context of absorbed‐dose protocols
Bibliographic record
Abstract
For reasons of phantom material reproducibility, the absorbed dose protocols of the American Association of Physicists in Medicine (AAPM) (TG-51) and the International Atomic Energy Agency (IAEA) (TRS-398) have made the use of liquid water as a phantom material for reference dosimetry mandatory. In this work we provide a formal framework for the measurement of absorbed dose to water using ionization chambers calibrated in terms of absorbed dose to water but irradiated in solid phantoms. Such a framework is useful when there is a desire to put dose measurements using solid phantoms on an absolute basis. Putting solid phantom measurements on an absolute basis has distinct advantages in verification measurements and quality assurance. We introduce a phantom dose conversion factor that converts a measurement made in a solid phantom and analyzed using an absorbed dose calibration protocol into absorbed dose to water under reference conditions. We provide techniques to measure and calculate the dose transfer from solid phantom to water. For an Exradin A12 ionization chamber, we measured and calculated the phantom dose conversion factor for six Solid Water phantoms and for a single Lucite phantom for photon energies between 60Co and 18 MV photons. For Solid Water of certified grade, the difference between measured and calculated factors varied between 0.0% and 0.7% with the average dose conversion factor being low by 0.4% compared with the calculation whereas for Lucite, the agreement was within 0.2% for the one phantom examined. The composition of commercial plastic phantoms and their homogeneity may not always be reproducible and consistent with assumed composition. By comparing measured and calculated phantom conversion factors, our work provides methods to verify the consistency of a given plastic for the purpose of clinical reference dosimetry.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".