Dosimetry with a phoswich detector
Bibliographic record
Abstract
A phoswich detector concept based on the combination of a high-Z element and a plastic element with a free running analogue-to-digital converter is presented in this work for the simultaneous measurement of operational dosimetric quantities H ∗ (10) and H ′ (0.07) in photon radiation fields. By means of a Pulse Shape Discrimination method and down to an energy of 60 keV ( 241 Am) in continuous photon radiation fields, the signal arriving at the common light sensor was separated into components coming from each element of the detector. In this context, crosstalk between the sensitive volumes represented an obstacle and was solved with a proper covering over one of the elements. Additionally, an algorithm for the calculation of the intended quantities based on the measured deposited doses was developed and tested using Monte Carlo methods with monoenergetic and X-ray radiation fields. Simulations set a validity region for the algorithm to the energy range between 20 keV and 3 MeV in the case of monoenergetic radiation and a lower energy cut of 15 keV in the case of X-ray fields. Furthermore, the algorithm was tested experimentally using 241 Am (60 keV) and 137 Cs (662 keV) sources against reference values from an OD-01 ionization chamber. Results showed a good sensitivity to the incoming photon energy, reflected in the variation of the ratio between the measured doses with the considered energies. At the same time, discrepancies between the measured and reference values of the operational quantities highlighted the need for a better calibration of the algorithm.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".