An NMR relaxometry and gravimetric study of gelatin-free aqueous polyacrylamide dosimeters
Bibliographic record
Abstract
In conformal radiation therapy, a high dose of radiation is given to a target volume to increase the probability of cure, and care is taken to minimize the dose to surrounding healthy tissue. The techniques used to achieve this are very complicated and the precise verification of the resulting three-dimensional (3D) dose distribution is required. Polyacrylamide gelatin (PAG) dosimeters with magnetic resonance imaging and optical computed tomography scanning provide the required 3D dosimetry with high spatial resolution. Many basic studies have characterized these chemical dosimeters that polymerize under irradiation. However, the investigation of the fundamental properties of the radiation-induced polymerization in PAG dosimeters is complicated by the presence of the background gelatin matrix. In this work, a gelatin-free model system for the study of the basic radiation-induced polymerization in PAG dosimeters has been developed. Experiments were performed on gelatin-free dosimeters, named aqueous polyacrylamide (APA) dosimeters, containing equal amounts of acrylamide and N,N'-methylene-bisacrylamide. The APA dosimeters were prepared with four different total monomer concentrations (2, 4, 6 and 8% by weight). Nuclear magnetic resonance (NMR) spin-spin and spin-lattice proton relaxation measurements at 20 MHz, and gravimetric analyses performed on all four dosimeters, show a continuous degree of polymerization over the dose range of 0-25 Gy. The developed NMR model explains the relationship observed between the relaxation data and the amount of crosslinked polymer formed at each dose. This model can be extended with gelatin relaxation data to provide a fundamental understanding of radiation-induced polymerization in the conventional PAG dosimeters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".