Applications of Polarization Imaging for Conventional and FLASH Radiotherapy Dosimetry
Bibliographic record
Abstract
Abstract The application of Cherenkov radiation in radiation therapy dosimetry has been limited by the anisotropic nature of the signal. Recently, polarization imaging was investigated as a method to correct Cherenkov anisotropy and allow precise dose measurements directly in a water tank. The aim of this study is to present polarization imaging as method for the measurement of ultra-high dose rate (UHDR) intra-operative electron beams. In this new approach, the polarized Cherenkov signal was isolated and utilized as a surrogate to evaluate the quality and consistency of both UHDR and conventional electron beams. Percent depth Cherenkov signal were measured for different energies, field sizes and dose rates. The results demonstrate high linearity (R 2 > 0.99) of the Cherenkov signal with the number of pulses and pulse width. The wide dynamic range of the device enabled measurement for both conventional and UHDR radiation beams making it a promising candidate for real-time quality assurance devices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".