An apparent threshold dose response in ferrous xylenol-orange gel dosimeters when scanned with a yellow light source
Bibliographic record
Abstract
Freshly prepared radiochromic ferrous xylenol-orange (FX) gels optically scanned with a light source exhibit a threshold dose response that is thermally and wavelength dependent. Correction for this threshold dose leads to accurate dose calibration and better reproducibility in multiple fraction radiation exposures. The objective of this study was to determine the cause of the threshold dose effect and to control it through improved dose calibration procedures. The results of a systematic investigation into the chemical cause revealed that impurities within the various FX gel constituents (i.e. xylenol-orange, gelatin, sulfuric acid and ferrous ammonium sulfate) were not directly responsible for the threshold dose. Rather, it was determined that the threshold dose response stems from a spectral sensitivity to different chemical complexes that are formed at different dose levels in FX gels between ferric (Fe(III)) ions and xylenol-orange (XO), i.e. Fe(III)i:XOj. A double Fe(III)2:XO1 complex preferentially absorbs at longer wavelengths (i.e. yellow), while at shorter wavelengths (i.e. green) the sensitivity is biased toward the single Fe(III)1:XO1 complex. As a result, when scanning with yellow light, freshly prepared FX gels require a minimum concentration of Fe(III) ions to shift the equilibrium concentration to favor the predominant production of the double Fe(III)2:XO1 complex at low doses. This can be accomplished via pre-irradiation of freshly prepared gels to a priming dose of approximately 0.5 Gy or allowing auto-oxidation to generate the startup concentration of Fe(III) ions required to negate the apparent threshold dose response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".