Spectral method for the correction of the Cerenkov light effect in plastic scintillation detectors: A comparison study of calibration procedures and validation in Cerenkov light‐dominated situations
Bibliographic record
Abstract
PURPOSE: The purposes of this work were: (1) To determine if a spectral method can accurately correct the Cerenkov light effect in plastic scintillation detectors (PSDs) for situations where the Cerenkov light is dominant over the scintillation light and (2) to develop a procedural guideline for accurately determining the calibration factors of PSDs. METHODS: The authors demonstrate, by using the equations of the spectral method, that the condition for accurately correcting the effect of Cerenkov light is that the ratio of the two calibration factors must be equal to the ratio of the Cerenkov light measured within the two different spectral regions used for analysis. Based on this proof, the authors propose two new procedures to determine the calibration factors of PSDs, which were designed to respect this condition. A PSD that consists of a cylindrical polystyrene scintillating fiber (1.6 mm3) coupled to a plastic optical fiber was calibrated by using these new procedures and the two reference procedures described in the literature. To validate the extracted calibration factors, relative dose profiles and output factors for a 6 MV photon beam from a medical linac were measured with the PSD and an ionization chamber. Emphasis was placed on situations where the Cerenkov light is dominant over the scintillation light and on situations dissimilar to the calibration conditions. RESULTS: The authors found that the accuracy of the spectral method depends on the procedure used to determine the calibration factors of the PSD and on the attenuation properties of the optical fiber used. The results from the relative dose profile measurements showed that the spectral method can correct the Cerenkov light effect with an accuracy level of 1%. The results obtained also indicate that PSDs measure output factors that are lower than those measured with ionization chambers for square field sizes larger than 25 x 25 cm2, in general agreement with previously published Monte Carlo results. CONCLUSIONS: The authors conclude that the spectral method can be used to accurately correct the Cerenkov light effect in PSDs. The authors confirmed the importance of maximizing the difference of Cerenkov light production between calibration measurements. The authors also found that the attenuation of the optical fiber, which is assumed to be constant in the original formulation of the spectral method, may cause a variation of the calibration factors in some experimental setups.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".