Sci‐Sat AM (1) General‐07: Water equivalent dosimeter array for small fields external beam radiotherapy
Bibliographic record
Abstract
Scintillation dosimeters consisting of a scintillating fiber coupled to an optical fiber and read with a CCD camera have shown accurate dose measurement in external beam radiotherapy. This work presents the next step, which is to investigate the development of a multi‐channel dosimeter array in conjunction with a CCD camera for dose measurement that includes small fields. The light collection of the CCD camera was studied to evaluate the number of detectors that can be read simultaneously. We also looked at possible sources of dose perturbation with a single‐fiber detector surrounded by other optical fibers. We then constructed a prototype array with 10 detectors and compared with measurements taken with small ion chambers. No dose perturbations were seen when a plastic optical fiber was used to transmit the scintillation light to the CCD. Depth dose curves measured in water with a scintillation dosimeter with up to 75 plastic optical fibers in the beam showed no discrepancy to within 0.3% when compared to the same curve taken with an ion chamber and without the plastic fibers. Agreement within 0.6% was seen for output factor measured with the scintillator and the A16 Exradin chamber for fields of 1×1 cm2 and 5×0.5 cm2. The ten‐fiber prototype allowed precise evaluation of profile and depth dose curves in a single irradiation. This work has shown that use of a multi‐channel scintillation dosimeter is feasible. The prototype of 10 detectors produced excellent results and could be extended up to 3000 detectors in the near future.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.080 | 0.025 |
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".