Characterization of the Uniformity of High-Flux CdZnTe Material
Bibliographic record
Abstract
for use in the detection of nuclear materials. CdZnTe is also of great interest to the photon science community for applications in X-ray imaging cameras at synchrotron light sources and free electron lasers. Historically, spatial variations in the crystal properties and temporal instabilities under high-intensity irradiation has limited the use of CdZnTe detectors in these applications. Recently, Redlen Technologies have developed high-flux-capable CdZnTe material (HF-CdZnTe), which promises improved spatial and temporal stability. In this paper, the results of the characterization of 10 HF-CdZnTe detectors with dimensions of 20.35 mm × 20.45 mm × 2.00 mm are presented. Each sensor has 80 × 80 pixels on a 250-m pitch and were flip-chip-bonded to the STFC HEXITEC ASIC. These devices show excellent spectroscopic performance at room temperature, with an average Full Width at Half Maximum (FWHM) of 0.83 keV measured at 59.54 keV. The effect of tellurium inclusions in these devices was found to be negligible; however, some detectors did show significant concentrations of scratches and dislocation walls. An investigation of the detector stability over 12 h of continuous operation showed negligible changes in performance.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".