Dose rate properties of NIPAM-based x-ray CT polymer gel dosimeters
Bibliographic record
Abstract
In this work we investigate radiation dose rate dependencies of N-isopropylacrylamide (NIPAM) based polymer gel dosimeters (PGDs) used in conjunction with x-ray computed tomography imaging for radiotherapy dose verification. We define four primary forms of dose rate variation: constant mean dose rate where beam on and beam off times both vary, variable mean dose rate where beam on time varies, variable mean dose rate where beam off time varies and machine dose rate (MU min(-1)). We utilize both small (20 mL) vials and large volume (1L) gel containers to identify and characterize dose rate dependence in NIPAM PGDs. Results indicate that all investigated constant and variable mean dose rates had negligible affect on PGD dose response with the exception of machine dose rates (100-600 MU min(-1)) which produced variations in dose response significantly lower than previously reported. Explanations of the reduced variability in dose response are given. It is also shown that NIPAM PGD dose response is not affected by variations in dose rate that may occur in modulated treatment deliveries. Finally, compositional changes in NIPAM PGDs are investigated as potential mitigating strategies for dose rate-dependent response variability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".