Development and characterization of the Hydra: a novel multi-headed, single optical channel scintillation detector
Bibliographic record
Abstract
Abstract Objective. Plastic scintillation detectors (PSDs) possess many properties (small size, water-equivalence, real-time reading) that make them well suited for dosimetric applications in radiotherapy. Multi-point PSDs (mPSDs) further enhance capabilities of PSDs, incorporating multiple detection points cascaded within a single collecting optical fiber in order to provide more spatial information about the radiation field. The goal of this study was to develop and characterize a novel mPSD design, called Hydra, that possesses multiple optical fiber heads connected to a single optical fiber. Each head tip includes a single scintillating element, allowing to measure the dose simultaneously at three independent locations in space. Approach. The Hydra design consists of three Medscint proprietary scintillators with emission peaks at 434, 428 and 530 nm. The optical fibers of each head and the collecting fiber are made of PMMA (ESKA GH-4001, Mitsubitshi Chemical Co., Tokyo, Japan). The Hydra was used to measure output factors, dose profiles and percent-depth-dose (PDD) curves in water under a 6 MV photon beam, individually for each head as well as with all three heads in the irradiation beam. Main results. The deviation on output factors, when all three heads are in the irradiation field, remains within ±1.1% as compared to when only 1 head is in the irradiation field. For the profile and PDD curves, the deviation with the reference curves remains within ±2% in the high-dose and low-gradient regions. Significance. The Hydra offers a good control on the uniformity of light intensity coming from each scintillator, a freedom to measure independently in a non-contiguous space, and an easier and more accurate calibration procedure compared to previous mPSD designs. These advantages open the door to new possibilities for multi-point dosimetry applications.
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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) | 0.000 | 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".