A 16-sensor prototype for brachytherapy in vivo dosimetry characterization
Bibliographic record
Abstract
The ORIGIN project (Optical Fiber Dose Imaging for Adaptive Brachytherapy) targets the production and qualification of a real-time radiation dose imaging and source localization system for both Low Dose Rate and High Dose Rate brachytherapy treatments. This goal will be achieved through a 16-fibre sensor system. Each fibre tip has been engineered to house a small volume of scintillating material to allow for measurements of the delivered dose. The instrument is based on Silicon Photomultipliers detectors, with a solution fully qualified on a single fibre prototype and currently being scaled up through the use of the CITIROC1A ASIC by WEEROC, embedded in the FERS-DT5202 scalable platform designed by CAEN S.p.A. The key features for a system such as ORIGIN, which aims to perform dose measurements in a clinical environment, are fibre response uniformity, system stability, high sensitivity, and perfect reproducibility. The commissioning of the 16-channel dosimeter system in laboratory conditions, with an X-ray cabinet, demonstrated reproducibility of measurements with deviations below 1% after the equalization procedure of the 16 sensors. Finally, the system performance, evaluated in clinical conditions (High Dose Rate centre, Belfast Hospital), allowed for valuable insight into the possible systematics which are present in the current system while simultaneously corroborating the validity of the equalization procedure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".