Development and characterization of a high resolution portable gamma spectrometer
Bibliographic record
Abstract
The recent disaster of Fukushima in Japan combined with the high demand to enhance nuclear safety and to minimize personal exposure to radioactive materials has a significant impact on research and development of radiation detection instrumentation. Currently, there is ample effort worldwide in the pursuit of radiation detection to maximize the accuracy and meet international standards in terms of size and specifications to enable radiation protection decision making. Among the requirements is the development of a portable, light-weight gamma-ray isotope identifier to be used by first responders in nuclear accidents as well as for radiation security and identification of illicit material isotopes. From nuclear security perspective, research into advanced screening technologies has become a high priority in all aspects, while for occupational safety, and environmental radiation protection, the regulatory authorities are requiring specific performance of radiation detection and measuring devices. At the applied radiation laboratory of the University of Ontario Institute of Technology the development of a high resolution spectrometer for medium and high energy gamma ray has been conducted. The spectrometer used a newly developed scintillator based on a LaBr3(Ce) crystal. The detector has been modeled using advanced Monte Carlo code (MCNP/X code) for the response function simulation and parameter characterization. The simulation results have been validated by experimental investigations using a wide range of gamma radiation energies. The developed spectrometer has been characterized in terms of resolution and response in different fields. It has also been compared with other crystals such as NaI(TI) and LiI(Eu).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".