Polyvinyl alcohol-Fricke hydrogel and cryogel: two new gel dosimetry systems with low Fe<sup>3+</sup>diffusion
Bibliographic record
Abstract
Two new Fricke dosimeter gel systems with low diffusion rates have been developed for 3D radiation dosimetry purposes. Both systems consist of a solution of 20% (by weight) polyvinyl alcohol (PVA) in a 50 mM H2SO4 solution with 0.4 mM ferrous ammonium sulphate and xylenol orange (FX). The difference in the two gels is the way that the gelation process was initiated: either by bringing the temperature to (a) +5 degrees C or (b) -20 degrees C before returning them to room temperature. These gels are termed 'hydrogel' and 'cryogel', respectively. The hydrogel is optically transparent, and can be used with either optical or MRI detection methods for dosimetric imaging. The cryogel is rubbery in texture but opaque, so its internal Fe3+ concentration can only be measured with MRI. The hydrogel's optical attenuation coefficient is linear (r2 = 0.99) with dose from 0 to 20 Gy with a sensitivity of 0.106 cm(-1) Gy(-1) (at 543 nm). In terms of MR relaxation rate, the dose response for both the hydrogel and cryogel was linear (r2 = 0.99) with a sensitivity of 0.020 s(-1) Gy(-1) (at 1.5 T). The Fe3+ diffusion coefficient (at 20 degrees C) was measured to be 0.14 mm2 h(-1), which is significantly lower than similar preparations reported for porcine gelatin or agarose. The PVA-FX gels can be stored for long periods of time before exposure to radiation, since the auto-oxidation rate was 10 times less than that of gelatin-Fricke recipes. The new gels developed in this work are a significant improvement on previous Fricke gel systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".