Accurate dose measurements using Cherenkov emission polarization imaging
Bibliographic record
Abstract
PURPOSE: Cherenkov radiation carries the potential of direct in-water dose measurements, but its precision is currently limited by a strong anisotropy. Taking advantage of polarization imaging, this work proposes a new approach for high-accuracy Cherenkov emission dose measurements. METHODS: , 6-, and 18-MV photon beam. Using Malus' law, the polarized portion of the signal is extracted. Corrections are applied to the polarized signal following azimuthal and polar Cherenkov emission angular distributions extracted from Monte Carlo simulations. Projected percent depth dose and beam profiles are measured and compared with the prediction from a treatment planning system (TPS). RESULTS: Corrected polarized signals on the central axis reduced deviations at depth (mean ± standard deviation) from 8% ± 5% to 0.8% ± 1% at 6 MV and 8% ± 7% to 1% ± 3% at 18 MV. For the profile measurement, differences between the corrected polarized signal and the TPS calculations are 1% ± 3% and 2% ± 3% on the central axis at 6 and 18 MV respectively. In these conditions, Cherenkov emission is shown to be partly polarized. CONCLUSIONS: This work proposes a novel polarization imaging approach enabling high-precision water-based dose measurements using the Cherenkov radiation. The method allows a correction of the Cherenkov emission anisotropy within 4% on the beam central axis and in depth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 teacher head, 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".