X‐ray CT dose in normoxic polyacrylamide gel dosimetry
Bibliographic record
Abstract
This study reports on the effects of x-ray CT dose in CT imaged normoxic polyacrylamide (nPAG) gel dosimeters. The investigation is partitioned into three sections. First, the CT dose absorbed in nPAG is quantified under a range of typical gel CT imaging protocols. It is found that the maximum absorbed CT dose occurs for volumetric imaging and is in the range of 4.6 +/- 0.2 cGy/image. This does scales linearly with image averaging. Second, using Raman spectroscopy, the response of nPAG to CT imaging photon energies (i.e., 120-140 kVp) is established and compared to the well known dose response of nPAG exposed to 6 MV photons. It is found that nPAG exhibits a weaker response (per unit dose) to 140-kVp incident photons as compared to 6 MV incident photons (slopes m6 mv = -0.0374 +/- 0.0006 Gy(-1) and m140 kVp = -0.016 +/- 0.001 Gy(-1)). Finally, using the above data, an induced change in CT number (deltaN(CT)) is calculated for nPAG imaged using a range of gel imaging protocols. It is found that under typical imaging protocols (120-140 kVp, 200 mAs, approximately 16-32 image averages) a deltaN(CT) < 0.2 H is induced in active nPAG dosimeters. This deltaN(CT) is below the current limit of detectability of CT nPAG polymer gel dosimetry. Under expanded imaging protocols (e.g., very high number of image averages) an induced deltaN(CT) of approximately 0.5 H is possible. In these situations the additional polymerization occurring in nPAG due to the imaging process may need to be accounted for.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".