Characterization of a water-based liquid scintillator for use in megavoltage radiotherapy beams
Bibliographic record
Abstract
Abstract The measurement of the dose delivered in radiotherapy treatments is carried out using dosimeters that are often expensive to produce and sometimes toxic to humans and the environment, which leads to more complex and rigorous clinical manipulations. It is in this context that it is necessary to provide new types of scintillators that would no longer have these problems while having properties equivalent to those of human tissues. Thus, the following study presents the performance of a water-based liquid scintillator used at radiotherapy energies. The characteristics studied include the proportionality of the scintillation signal to the dose, the scintillation efficiency at two different energies as well as the identification of the Cherenkov portion of the signal for photon beams of 180 kVp, 6 MV as well as 18 MV. Spectral measurements of the scintillation solution and a solution of distilled water were acquired in order to isolate the contribution of the scintillation signal from the spectrum obtained, and then compared to a commercial scintillator, Ultima Gold. The signal exhibits a linear dose relationship with a correlation coefficient of 0.999 and lower scintillation efficiency than Ultima Gold.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".