Poster — Thur Eve — 06: Radiochromic Film Densitometry with Vista15 Optical Cone Beam CT Scanner
Bibliographic record
Abstract
Purpose: To examine the performance of a scatter corrected commercial optical cone beam CT scanner, Vista15™, adapted for radiochromic film dosimetry. Methods: A slotted film mask adjacent to the EBT2 film was used to generate alternating open and dark areas. Three images were acquired with the mask centered along the optical axis and offset +/−0.7cm. The masked transmission images were processed by first forming composite images from the open and shadow areas of the three image sets. The composite shadow image was subtracted from the corresponding open image to create a “glare‐free image”. Net optical density (OD) images were generated by calculating −log10 (corrected post/corrected pre image). The calibration dose response in EBT2 film using multiple 4MV photon fields and a single 12MeV electron field was measured. Results: In the corrected data, net OD increased and the buildup region mirrored actual 12MeV dose deposition in water. This trend was also observed in the multiple 4MV photon field calibration data. From comparing the two calibration techniques, a discrepancy in net OD of up to 4% was observed. This suggests that EBT2 film users should have a consistent method for calibrating the dose response. Conclusions: The emission spectrum of Vista15™ designed for readout of radiochromic gels and plastics overlaps the absorption peak in EBT2 films, thus, making this scanner convenient and economical for both planar and 3D dosimetry. A method for veiling glare correction is promising but a more complex multiple grid approach will be needed in order to achieve quantitative densitometry.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".