Survey Meter Using Novel Inorganic Scintillators
Bibliographic record
Abstract
Single crystal scintillator materials are widely used for detection of high-energy photons and particles. There is continuous demand for new scintillator materials with higher performance because of increasing number of medical, industrial, security and other applications. This article presents the recent development of three novel inorganic scintillators; Pr-doped Lu3Al5O12 (Pr:LuAG), Ce doped Gd3 (Al, Ga)5 O12 (Ce:GAGG) and Ce or Eu-doped 6LiCaAlF6 (Ce:LiCAF, Eu:LiCAF). Pr:LuAG shows very interesting scintillation properties including very fast decay time, high light yield and excellent energy resolution. Taking the advantage of these properties, positron emission mammography (PEM) equipped with Pr:LuAG were developed. Ce:GAGG shows very high light yield, which is much higher than that of Ce:LYSO. Survey meter using Ce:GAGG is developed using this scintillator. Ce:LiCAF and Eu:LiCAF were developed for neutron detection. The advantage and disadvantage are discussed comparing with halide scintillators. Eu-doped LiCAF indicated five times higher light yield than that of existing Li-glass. It is expected to be used as the alternative of 3He.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".